As the US moves to integrate more AI systems into every arm of its military, the situations on the ground in the Middle East are raising some serious problems for maintaining the compute and connectivity needed to keep systems online.

Drones, sensors, AI-assisted targeting and decision-making all rely on these systems in one way or another, and the destruction of a single frontline AI data center can seriously damage an army’s capacity to function.

But these problems go beyond hardware. How does a drone adapt its mission parameters without being able to communicate? How can AI models continue inference without access to critical battlefield data? And what compromises must be made to prepare battlefield AI for these conditions?

Battlefield AI should continue functioning, even when comms go down or hardware is disabled

While the conflict circling the Strait of Hormuz may be a hugely expensive endeavour, Iran is providing valuable lessons for warfighters. Relying on traditional data centers in the Middle East has already shown its weaknesses. These sprawling warehouses make easy targets for cheap missiles, and entire systems can be taken offline from a single hit.

Palantir has already begun deploying shipping containers filled with Nvidia hardware as an alternative to the traditional data center. These containers can be deployed on frontlines and can connect directly into operational workflows, offering decentralized compute where it is needed most.

Scaleout is a company building infrastructure for edge AI and federated learning that trains models on distributed, sensitive data without centralising it. The company has worked with NATO - most recently the Swedish Air Force - and defense primes such as BAE Systems.

Andreas Hellander is the CEO and co-founder of Scaleout. He holds a PhD in Scientific Computing and an MSc in Biotechnology Engineering, and is an Associate Professor at Uppsala University, where he built one of the top research groups at the Department of Information Technology before founding Scaleout.

I spoke to Andreas to learn more about how battlefield AI systems can be made more resilient, and how drones, sensors, and other frontline technologies can continue functioning when conditions go downhill.

• What happens when parts of a battlefield AI's computing and hardware are taken offline? What redundancies are in place to keep communications between systems operational?

The aim is not to promise an unbreakable connection; it is to stop the loss of one component from taking down the whole capability. In our architecture, a disconnected node continues local inference using its last approved model, caching detections and telemetry until a link returns.

Multiple aggregation points can be used above the edge. If one becomes unavailable, clients can be reassigned and training can proceed with those still reachable. That creates graceful degradation rather than an all-or-nothing failure. We do not supply the tactical communications network itself; our job is to ensure the AI workload does not assume that any radio, satellite or other link will always be available.

• What are the trade-offs between a highly centralized battlefield AI network and a more distributed approach, especially concerning data gathering, targeting, battlefield coordination and logistics?

Centralisation provides a consistent operational picture, substantial compute and a clear place to enforce security, model approval and command policy. It supports theatre-wide coordination and logistics, but also concentrates risk: losing one link or facility can remove a disproportionate share of the capability, while moving large or classified datasets may be slow, prohibited or impossible.

A distributed system keeps analysis close to the sensor, reducing latency and allowing local functions to continue during disconnection. The trade-off is fragmentation. Targeting based on a partial or stale picture is risky, and local logistics decisions may not be optimal for the wider force. The best design is usually hybrid: central coordination when available, with clearly bounded local capability when it is not. Authority remains with the relevant command-and-control and human decision process.

• How do these AI drones and sensors adapt to the battlefield and what differences are there in the behavior of an AI drone that can still communicate and one that has lost communication?

It is important to separate running a model from retraining it. Small platforms typically perform inference in flight, while controlled retraining and approval happen on a ground node or more capable edge computer. Onboard learning exists in research, but uncontrolled mid-mission retraining creates serious assurance problems.

A connected platform can share detections, receive tasking and contribute to a wider operational picture. After losing its link, a drone follows its pre-approved failsafe: depending on the mission, it may continue a bounded task, return, hold or land. Onboard processing can keep perception and navigation working, but the platform loses external context, new instructions and fleet coordination. Disconnection should be a designed operating state with explicit limits, not an improvised emergency mode.

• How is the data collected by these drones and sensors used to help battlefield AI systems adapt to new conditions, threats, and tactics?

The useful data is often the hardest to move, so we send the model to the data rather than centralising the footage. Active-learning software identifies the frames most likely to improve it, such as uncertain detections, unfamiliar objects or changed conditions. A person still labels the selected material; the software reduces the searching, not the need for human judgement.

The model is then fine-tuned locally and tested against a benchmark. A candidate can also run beside the current model in shadow mode before an operator approves it. Where policy and connectivity allow, sites exchange protected model updates rather than raw training footage, combining them into a shared model. Federated learning reduces data movement, but the updates still need to be secured, validated and audited.

• What are the main challenges you encounter when deploying AI drones and sensors? What capabilities are available for militaries to source the required compute and energy production close to the front lines?

The hardest constraints are usually power, heat, weight, weather, vibration, electronic warfare, inconsistent data and safe software updates across a mixed fleet. Integration and accreditation can be as demanding as the machine learning.

The compute is commercially available: low-power modules such as NVIDIA Jetson for small platforms, and ruggedised GPU servers or containerised edge units for ground sites. Energy is tougher. Every processor competes with propulsion, sensing and communications, while generators, batteries and distribution equipment add logistical burden and new points of failure. In our public demonstration with BAE Systems Bofors, the perception workload ran on onboard compute at -18°C without connectivity. The principle is to use the smallest practical footprint and assume both power and bandwidth are scarce.

• There is an increasingly blurred involvement of commercial companies providing services for military use, such as AWS data centers in the Middle East and drone production in the UK for Ukraine. How are companies providing services to the military adapting to the pressures of potentially being deemed a legitimate military target?

Speaking for Scaleout, rather than for the sector as a whole, we design our platform so that a customer’s operation does not depend on Scaleout remaining continuously available. It runs in the customer’s own infrastructure, works air-gapped, and does not require a licensing call-home or persistent connection to our systems or a public cloud.

That matters in any contested or disconnected environment: reliance on a remote provider can become an operational vulnerability. Our approach has therefore been to keep control and continuity local to the customer, rather than make our own infrastructure a critical dependency.

The wider question of how commercial providers are viewed in a conflict is one for policymakers, legal experts, and the companies involved. We would not want to speculate about other providers’ risk assessments or operating models.

• What is the future trajectory of these systems? Will each individual drone and sensor have its own connectivity that can feed data back through a global satellite network? Will these systems be able to operate autonomously for multiple days or weeks without human input?

Connectivity will improve, including through low-Earth-orbit satellites, but connecting every sensor directly to space is unlikely to be the universal answer. Terminals consume power and spectrum, add cost and can create an electronic signature. A more resilient pattern combines local mesh links, opportunistic synchronisation and selected gateways to satellite or other long-range communications.

Longer disconnected operation is realistic, but endurance is often limited by batteries, weather and maintenance rather than AI software. There is also a critical distinction between operating without a connection and operating without human authority. The first is a resilience property; the second is a policy, legal and ethical decision. The future is therefore not simply more autonomy, but verifiable control: knowing which model ran on each platform, what produced it, where its limits were and who approved it.

OpenAI has unveiled a much anticipated AI model which the firm has dubbed ‘GPT-6 Astra’. While the model has improved significantly across benchmark testing and brings a host of new business features, there is still a dark cloud looming over the new model.

Off the back of OpenAI’s accidental hack of Hugging Face and the company’s subsequent efforts to improve how AI agents behave and interact, numerous cybersecurity experts have raised concerns about the model’s new ‘recurrent depth’ reasoning capabilities.

This new reasoning architecture allows the model to consider a problem multiple times before taking an action, compared to the standard chain-of-thought reasoning used in previous models.

Why the concern about recurrent depth reasoning?

This new level of reasoning apparently offers improved performance. OpenAI also says it has fixed its models' abilities to circumvent boundaries when performing tests by monitoring the models reasoning and ensuring the model stays aligned within the scope of its task.

During Astra’s launch event, OpenAI chief scientist Jakub Pachocki said: “We will not accept degradation in our ability to monitor model alignment beyond a certain level. We will withhold scaling until we can regain enough confidence.”

But numerous experts believe that the lessons of the Hugging Face incident have not yet been learned, and the model has been released without adequate testing on Astra’s reasoning and monitoring.

After all, no one thought one of OpenAI’s models could set up a hidden internet-connected messaging board that allowed AI agents to influence each other's behavior.

But with Astra being released into the real world, the lessons may have to be learned on the fly.

Expert perspectives on OpenAI Astra release

• James Blake, VP of Global Cyber Resiliency Strategy at Cohesity:

The launch of Astra is raising questions again around the safety of Frontier AI. Instead of simply asking whether a model is "safe", organisations now need to ask whether it remains safe across millions of different situations, prompts and interactions. Cyber resilience has traditionally assumed that systems and threat actors behave deterministically. AI systems don’t.

Advanced models can and will continue to exhibit behaviours that emerge from their optimisation process rather than from explicit programming. We have to move beyond thinking about AI as just another software tool and find ways to ensure these systems remain observable, auditable and governable throughout their lifecycle.

The most important question we’ll need to answer in future is one of liability. Suppose an AI system autonomously develops a strategy that causes financial loss, leaks confidential information or violates regulation. Who is responsible? The developer that trained the model? The cloud provider operating the infrastructure? Currently the answer is surprisingly unclear. It’s not just about what AI can do: it’s about who is accountable when it does something nobody expected.

• Oleksandr Yaremchuk, Co-Founder & CTO at Manifold Security:

OpenAI is calling Astra its most aligned model yet, even as its chief scientist admits monitorability is getting harder as models get more capable. Evidently, Astra hides its reasoning in the majority of tested cases, and some successful attacks left no reasoning trace at all. That's the tool many organisations still use, including the labs themselves, for auditing what an agent is doing, and it's getting less reliable with every release.

That matters because Astra isn't staying inside OpenAI's test environment. It's going to run as an agent on employee laptops and in the browser, holding real credentials, inside companies that have no way to watch what it does once it's there. A model that explains itself less isn't more aligned, it's just harder to catch when it goes wrong.

Labs can keep debating what these models say or refuse to say. Security teams need to stop relying on that and start monitoring what agents actually do at runtime, with the ability to shut one down mid-action. That's the only oversight left that still works once the reasoning goes quiet.

• Kristin Lowery, Field CISO at Optiv:

For boards and executive leaders, the emergence of OpenAI’s Astra model highlights a broader reality: AI is no longer just a productivity issue; it is a risk management issue.

Just as organizations established governance for cloud adoption and digital transformation, they now need clear policies, strong oversight, and accountability for AI use.

The question is not whether AI will become more capable — it will. The real challenge is whether organizations can strengthen their governance, security controls, and workforce readiness quickly enough to keep pace.

• Patricia Titus, Field CISO at Abnormal AI:

OpenAI crossing this threshold deserves attention. Credit where it's due, they're handling it responsibly by restricting Astra's advanced cyber capability to a small coalition rather than releasing it broadly.But this isn't one company's problem to contain.

Once a model can find and exploit unknown flaws without a human in the loop, that capability doesn't stay exclusive for long. Open-weight and modified models typically trail the frontier by only months, and that's the reality defenders have to plan around now.

Static, signature-based defences were built for attacks that repeat. They weren't built for an adversary that generates a new one every time. Defenders need the same shift, systems that learn what normal looks like for every identity, human, machine, or AI agent, and flag and contain the moment something deviates, at machine speed.

The window to build that is open now. It won't stay that way once this capability is common instead of rare.

• Raghu Nandakumara, VP of Industry Strategy at Illumio:

With the Astra announcement, OpenAI is doubling down on monitoring the model's own behaviour – a response to the model "breakouts" seen over the past few months.

When Anthropic announced Claude Mythos Preview, the core concern was the model falling into the wrong hands. OpenAI's answer goes further adding guardrails around the model's own reasoning and actions, regardless of the user's intent. The goal is to catch a model going rogue mid-task, not just stop it being misused at the outset.

The rest of this announcement can be summarised as ‘we have a new frontier model, and it’s more capable than the last one’.

For a budget business monitor in the Labor Day sales, the one that stands out to me is the Philips 24-inch 241V8LB, which is down to $75 (was 90) at Amazon.

To me, this is the perfect display for anyone working from home, who doesn't need ultra high-resolutions or massive screens that take up half the desk.

Don't let the price fool you. It's not entirely feature-free. Budget monitors in this range usually cap out at 60Hz or 75Hz, so the jump to an above-average 100Hz with Adaptive Sync is a genuine step up for everyday use, whether that's office work, browsing, or even light gaming.

Why we recommend it

At under $75, most competing monitors settle for a 60Hz or 75Hz panel. The 241V8LB's 100Hz refresh rate with Adaptive Sync makes everyday scrolling and window movement noticeably smoother, and it's enough of a step up that it's worth seeking out even for buyers who aren't gaming.

The VA panel trades some of the wide-angle color consistency of an IPS display for deeper blacks and stronger contrast, which suits office and productivity use well. Philips also backs the 241V8LB with a 4-year advance replacement warranty, longer than the 1 to 3 years typical of budget monitors in this price bracket.

The nearly frameless design on three sides is a small but useful touch for anyone running two or more of these side by side, keeping the visual gap between screens to a minimum.

Price Context & Historical Value

A $15 drop from $89.99 to $74.99 is a modest discount in percentage terms, around 17 percent off. It isn't a dramatic markdown, but the 241V8LB is already positioned as a budget monitor, so this price puts it firmly among the cheaper 24-inch 100Hz options available right now.

Should you buy it?

✅ Buy the Philips 241V8LB if... you want an affordable 24-inch monitor for everyday office or home use, you'd like a 100Hz refresh rate and Adaptive Sync instead of a standard 60Hz panel, or you're setting up a multi-monitor desk and want a nearly frameless design.

❌ Skip the Philips 241V8LB if... you need an IPS panel for wide-angle color accuracy, you want a resolution higher than 1080p, or you need USB-C or DisplayPort inputs rather than HDMI and VGA.

The Catch: What to know before you buy

This is a 1080p VA panel, not an IPS display, so colors will shift somewhat at extreme viewing angles compared to pricier alternatives. Connectivity is limited to a single HDMI 1.4 port and VGA, with no USB-C or DisplayPort, so it's worth checking that fits your setup before buying.

• See the full Labor Day sale at Amazon

We've tested plenty in the Anker Solix line of portable power stations, and they've continually impressed us. And as part of the Labor Day sales, the Anker Solix S2000 has dropped to $650 (was $1199) at Amazon.

The 2,010Wh power station is smaller and lighter than other units in its capacity class, aimed squarely at everyday home backup. It's capable of keeping a fridge, router, or medical device like a CPAP machine running through an outage rather than powering a whole house.

Why we recommend it

Most 2kWh power stations in this category are large enough that finding a permanent spot for one becomes part of the decision. Anker built the S2000 to be around 30% smaller and 25% lighter than the typical unit at this capacity, at 35.7lbs, which makes it easier to tuck into a closet, under a desk, or beside a fridge without it dominating the room.

The battery itself is the bigger story. Anker rates the S2000's LiFePO4 cells for 10,000 charge cycles, roughly two to three times the 3,000 to 4,000 cycle rating common on rival units in this class, with a stated 15-year lifespan. For a device meant to sit ready for years between outages, that longevity matters more than most spec sheets suggest.

Idle power draw is another area where the S2000 stands out. Anker's OptiSave feature keeps standby consumption down to around 6W with outputs enabled, which means less of the stored capacity is wasted just keeping the unit ready. Combined with a 10-millisecond UPS switchover, it's built to keep a fridge or router running through a power cut without a noticeable interruption.

At 1,500W continuous output across five AC outlets, it covers the large majority of everyday household devices, and Anker's SurgePad feature can support compatible appliances needing up to 2,600W in short bursts.

For more top-performers we've tested, see our guide to the best portable power stations.

Also consider

Price Context & Historical Value

A $550 drop from the $1,199.99 MSRP is a steep discount on paper, around 46 percent off, though it's worth knowing the S2000 has rarely sold at full price since launch. It's generally traded between $600 and $700 over the summer, with a low of around $600 during a Prime Day promotion. At $649.99, this is a solid, near-best price rather than a one-off record low, so it's a good time to buy without being a once-ever deal.

Should you buy it?

✅ Buy the Anker Solix S2000 if... you want dependable home backup power in a compact, lightweight 2kWh unit, you need UPS-style protection for a fridge or a medical device like a CPAP machine, or you value a long-lasting LiFePO4 battery over raw output.

❌ Skip the Anker Solix S2000 if... you need to run high-draw appliances like a microwave or window AC unit, you want a system that's expandable with add-on battery packs, or you would rather wait for more independent hands-on testing before buying.

The Catch: What to know before you buy

The 1,500W continuous output also trails some higher-wattage rivals in this capacity class, and the S2000 isn't expandable with additional battery packs the way some competing systems are, so it's worth checking your intended appliance loads before buying if you're planning on anything beyond basic home backup.

• Shop the full Labor Day sale at Amazon

• Nvidia's NVHBM moves the memory controller off the accelerator die and into the HBM stack's base die, allowing it to claim a potential 30% more bandwidth, 15% lower HBM power, and 25% more compute area versus standard HBM4E
• Nvidia's NVHBM performance comparisons are linked to HBM4E, which is still in the sampling stage, with a launch expected sometime in 2027
• Access to the custom solution is gated behind NVLink Fusion; Amazon's Annapurna Labs is the only named partner so far and has not said which GPU uses that memory

On August 26, Nvidia extended its NVLink Fusion program with NVHBM, a custom high-bandwidth memory architecture that the company says delivers up to 30% more memory bandwidth per stack, 15% lower HBM power consumption, and up to 25% more usable area on the accelerator die.

The performance was measured against standard HBM4E samples even as the memory is expected to ship in volume some time in 2027.

Amazon's Annapurna Labs is the first named partner for Nvidia's memory advance which aims to address growing performance limitations for frontier-level AI models centering around limited bandwidth.

What makes NVHBM tick?

Nvidia's approach doesn't reinvent how memory is handled; it reimagines where it is managed. Conventional HBM approaches split this between two companies: the memory vendor supplies the DRAM stack and its base die, and the accelerator designer puts the memory controller and physical interface on its own compute die.

JEDEC standardizes the connection between the two at the cost of a very wide, comparatively slow parallel bus. NVHBM dissolves the seam altogether by moving Nvidia's memory controller into the base die of the 3D stack, replacing the standard bus with a narrower, serialized die-to-die link that Nvidia designs and memory makers can build.

Nvidia's technical blog puts the resulting reduction in interface and support area at up to 67% against the JEDEC HBM4E standard, even as it improves key power consumption, memory bandwidth, and usable area.

The underlying tech is not completely new, however: Marvell announced the same basic idea in December 2024, naming Micron, Samsung, and SK hynix as collaborators while claiming up to 25% more compute area, 33% greater memory capacity, and a 70% reduction in memory interface power, figures that come close to what Nvidia is currently projecting. Counterpoint Research analyst Neil Shah put it plainly: "The technology is not new. The distribution is."

Even as HBM4E remains elusive, as it is not in mass production just yet, with Samsung shipping the first HBM4E samples in late May 2026 and SK hynix pulling its own sampling forward to around June, NVHBM is even more elusive. It is a building block gated behind NVLink Fusion, Nvidia's program for connecting third-party accelerators to its rack-scale platform, and access runs through that program's partner list.

Amazon's Annapurna Labs is the first named participant, with Nvidia's blog saying Annapurna will support NVLink Fusion with Trainium4 without explicitly mentioning NVHBM.

For now, NVHBM might be the future, but it may arrive well after HBM4E is already being deployed en masse. Nvidia's own technical blog describes NVHBM as built on the same technology the company will use for future GPUs, without specifying the first generation that would support it natively.

• Google released Chrome 152.0.7977.82/.83 for Windows, Mac, and Linux
• Patch fixes 12 flaws, including zero‑day CVE‑2026‑85046 (type confusion in V8)
• Sixth Chrome zero‑day this year; Chromium browsers also affected, update urged immediately

Google has released a new version of its Chrome browser for Windows, Mac, and Linux, fixing a dozen of vulnerabilities. Among them is a high-severity flaw that is being actively exploited in the wild.

In a security advisory published on the Google blog on September 3, the search engine company said Chrome’s newest version is now 152.0.7977.82/.83 for Windows and Mac, and 152.0.7977.82 for Linux.

Rollout is expected to be gradual, so make sure to check if you already received it. Most of the time the update is automatic and instant and if you’re not certain, tap the three vertical dots in the top-right corner of the browser and choose Help. Navigate to About Google Chrome and there you will find the version number.

Running malicious code remotely

This patch fixes a total of 12 vulnerabilities, most of which are graded as high severity. Among them is a “type confusion in V8” bug, discovered by security researcher Salvatore Gulizia.

For his effort, Gulizia was awarded $1,000. Apparently, this bug is being actively leveraged in real-life attacks, although Google (as usual) decided not to share the juicy details until the majority of browsers are protected.

The vulnerability is tracked as CVE-2026-85046. On the National Vulnerability Database (NVD), it is described as a “type confusion in V8 in Google Chrome [that allows] a remote attacker to execute arbitrary code inside the sandbox via a crafted HTML page.”

V8 is Chrome’s JavaScript engine which allows web apps and interactive websites to run in the browser. Those interested in the technical breakdown of the vulnerability can find it on Guzlia’s blog.

You can find the full list of fixed vulnerabilities on this link.

This is the sixth zero-day Google fixed in Chrome since the start of the year. It also affects other browsers built on Chromium, so if you’re running Edge, Brave, Opera, or Vivaldi, make sure to update to the latest version as soon as possible.

Via The Hacker News

If you're building a new PC or upgrading an aging boot drive, you'll definitely want to check out the Kingston NV3 1TB internal SSD, now $157 (was $216) at Newegg.

An established name in the storage arena, Kingston built the NV3 as the successor to its popular NV2 line, and the jump to a Gen 4x4 controller brings a meaningful speed increase - it can hit read speeds up to 6,000MB/s.

But it keeps the single-sided, compact M.2 2280 form factor that fits easily into laptops and small-form-factor builds.

Why we recommend it

The headline number is up to 6,000MB/s of sequential read performance, and independent testing has generally found the NV3 hits close to its rated speeds, putting it in the same territory as several established TLC-based drives despite using cheaper QLC NAND.

Kingston keeps costs down with a DRAM-less design that relies on Host Memory Buffer, borrowing a slice of system RAM instead of including a dedicated cache chip. For typical use, booting, loading applications, and gaming, that trade-off is barely noticeable, and it's part of how Kingston is able to price the NV3 competitively.

The single-sided M.2 2280 layout keeps the drive slim enough for thin laptops and small-form-factor desktops, and Kingston's reputation for reliable, mainstream storage gives some reassurance on a component you don't want to think about after installing it.

Price Context & Historical Value

A $59 drop from $215.99 to $156.99 is a substantial discount, around 27 percent off, on a capacity and speed class that typically runs cheaper than this. It's worth double-checking Newegg's price at checkout since SSD pricing shifts often, but this discount looks like a genuine markdown rather than an inflated list price.

Should you buy it?

✅ Buy the Kingston NV3 1TB if... you want a fast, affordable PCIe 4.0 boot drive for a new build or upgrade, you need a compact single-sided M.2 2280 drive with low power draw, or you're a mainstream user whose workloads are mostly reads rather than sustained large writes.

❌ Skip the Kingston NV3 1TB if... you regularly write very large files such as video footage and need consistent sustained write speeds, you want a drive with a dedicated DRAM cache rather than Host Memory Buffer, or you need more than 1TB in a single drive.

The Catch: What to know before you buy

This is a QLC, DRAM-less drive, so sustained write performance drops noticeably once its SLC cache fills, which matters most for large, continuous file transfers rather than everyday use.

• See all Labor Day deals at Newegg

• OpenAI rolled out GPT‑6 Astra, its most advanced AI, with “critical” cyber capabilities
• Astra can autonomously find and exploit unknown flaws; release limited to vetted Daybreak participants
• Staggered rollout sparked user frustration; Altman apologized, promising broader access soon

OpenAI has begun rolling out GPT-6 Astra, its latest and most capable artificial intelligence model.

In an announcement published on its website, OpenAI said Astra represents a “significant step up in cyber capabilities”, meeting the company’s “Critical” threshold.

This threshold, the company explained, means that under the right circumstances, the tool can find “previously unknown security flaws and develop new ways to exploit them across many well-protected systems without a person guiding each step.”

Apologies for a messy rollout

OpenAI also said Astra improves on functions such as computer use, software engineering, and science, and that it should be better at staying oriented, compared to previous versions.

Just like many of the previous models, Astra’s release has been marred with controversy. Roughly a month ago, OpenAI said the model’s “critical” cybersecurity capabilities prompted it to pause some internal development and trigger safety protocols.

In response to early findings, the company scaled up certain security controls and even paused activities that do not meet its newly established security requirements.

It now decided it was time to release the model, but still not to the general public. Instead, it opted for a staggered release, giving it first to a limited group of companies participating in the Daybreak program, a cybersecurity initiative that gives vetted organizations (cybersecurity and otherwise) specialized AI tools for vulnerability research and threat detection.

This did not sit well with many ChatGPT users, especially those paying a monthly subscription. As The Verge reported, CEO Sam Altman was apologizing, mere hours after launch, for the “messy rollout” of Astra.

Initially, all Plus, Pro, Business, and Enterprise users were supposed to gain access to Astra, as well as those accessing through OpenAI API, Microsoft Azure, and AWS Bedrock.

“We are working towards getting Astra in everyone’s hands as quickly as we can,” Altman said on X. “I know it is frustrating and I appreciate the patience. It should be quick.”

Via CNBC

• Texas has gone from being pro-data center to anti-expansion
• Communities have had enough of rising prices and strained supplies
• AI data centers have been described as this election season's core fight

Republican politicians Texas are starting to turn against the rapid expansion of AI data centers, marking a major shift in attitude against backing Trump's push for the US to dominate the global AI race.

Candidates from the party in at least five states have recently shared stances that counter the current administration's goals as citizens continue to be concerned about impacts like rising bills.

Nowhere is this more noteworthy than the state of Texas, which houses OpenAI's flagship Stargate campus.

Republicans are starting to speak out against rapid data center expansion

The state's governor, Greg Abbott, has undergone a particularly significant change in position. Less than a year ago he described Texas as the "epicenter of AI development," but his campaign for re-election now calls for new restrictions including regulation, reduced tax incentives, restrictions in rural communities and resource consumption measures to protect household bills.

With local opposition so poignant amid ongoing data center expansions globally, Abbott's Democratic counterpart, Gina Hinojosa, also described data centers as "the fight of this election season," making them much more of a political weight than early investors might previously have expected.

Opposition is being driven largely by concerns about the local costs – not an opposition to AI itself. Americans have already seen rising electricity bills, strained water supplies and light and noise pollution.

Ultimately, Texas has shown us how concerns over power prices, water consumption, tax breaks and more can turn technology companies and their projects into serious political cases. And looking ahead, with backlash now spanning both major parties, it's clear that technology companies will need to do more than offer employment opportunities to win over local communities.

Via Reuters

If you're picking up a 10GbE NAS device like the Ugreen NASync DXP6800 Pro, now $1100 at Amazon, you'll need suitably fast networking hardware if you want to take advantage of those speeds.

So, I'd strongly recommend grabbing the TRENDnet TEG-S762 switch for $92, which has two 10GbE RJ45 ports alongside four 2.5GbE connections.

Connecting the NAS to one of the switch's 10GbE ports gives it a much faster route to other compatible devices on your network. That can substantially reduce the time it takes to transfer large backups, photos, and video files compared with using standard Gigabit Ethernet.

Why we recommend these two products

The DXP6800 Pro goes well beyond basic network storage. Its 10-core Intel Core i5-1235U processor and 8GB of DDR5 memory give it plenty of processing power, and the RAM can be expanded to 64GB if your requirements grow.

The powerful unit features dual 10GbE ports for those faster speeds. You get six SATA drive bays plus two M.2 NVMe slots, along with two Thunderbolt 4 ports. It supports RAID 0, 1, 5, 6 and 10, as well as JBOD and Basic configurations, giving you plenty of flexibility when deciding how to balance capacity, performance and redundancy.

The TRENDnet TEG-S762 is a particularly good match because its two 10GbE RJ45 ports let you take advantage of the NAS's high-speed networking rather than limiting it to slower Gigabit or 2.5GbE connections.

Price context & historical value

The diskless Ugreen NASync DXP6800 Pro has previously dropped as low as $969.99 earlier this year, so this isn't the best price we've seen. But it's the best price we've seen at the moment. For comparison, it's currently the same price at Newegg, too.

The TRENDnet TEG-S762 adds another $92 to the cost, but that's a relatively small addition alongside a four-figure NAS if you don't already have suitable networking hardware. It also lets you connect other compatible devices through its four 2.5GbE ports. It has been cheaper in the past, but only by a few dollars.

Should you buy it?

✅ Buy the NAS and switch together if...

You regularly work with large amounts of data and need fast centralized storage for photography, video editing or other creative work. The combination makes sense if several computers or other devices need regular access to the same large project files.

❌ Skip the NAS and switch together if...

You only need somewhere to back up documents, photos and other everyday files. A six-bay NAS with a Core i5 processor, Thunderbolt 4 and high-speed networking is overkill for basic home storage, and a considerably cheaper two- or four-bay model should be sufficient.

The Catch: What to know before you buy

Ugreen's DXP6800 Pro is diskless, so the $1,099.99 price doesn't include any hard drives. Filling six bays with high-capacity NAS drives can easily add a substantial amount to the final cost, particularly if you want enough drives for a RAID configuration.

You'll also need suitable networking hardware if you want to use its 10GbE capabilities. The TRENDnet TEG-S762 provides the necessary 10GbE RJ45 connection without requiring an SFP+ adapter, while its fanless design makes it particularly suitable for a home office or studio.

• Shop all products in Newegg's Labor Day sale

OLED monitors are great for creative work, but they don’t tend to be cheap. I’ve found a major deal on the 27-inch ASRock Phantom monitor (PGO27QSA) for $300 (was $465) at Newegg for Labor Day.

For your money you get a QHD OLED panel (2560 x 1440) with HDR10 support, a 0.03ms response time, a wide range of ports and a fully adjustable stand. On the content creation side, the all-important color coverage hits 99% DCI-P3 color coverage, with factory calibration of Delta E < 2 out of the box.

Why we recommend it

The big attraction of this monitor is the OLED panel, which can individually control its pixels rather than relying on a separate backlight. This allows it to produce genuinely deep blacks and excellent contrast that can be particularly useful when you're creating or editing visual content.

At 27 inches, QHD provides a good balance between desktop space, image detail and physical size. The 2560 x 1440 resolution provides considerably more working space than Full HD. For content creators, it boasts 99% DCI-P3 color coverage and Delta E < 2 factory calibration.

For more options, take a look at our roundups of the best gaming monitors and the best monitors for work, gaming and more.

Price context & historical value

$299.33 appears to be the lowest price so far for the ASRock Phantom monitor at Newegg. That's particularly impressive given that it only arrived at the retailer recently with a $465 price tag. The previous low was $333.33 last month.

Should you buy it?

✅ Buy the 27-inch ASRock Phantom Gaming monitor if...

You work with photography, video or other visual content and want to move from an LCD to OLED without spending a fortune. You also get HDMI 2.1 and DisplayPort 1.4 connectivity, with two of each ports providing plenty of flexibility for connecting multiple computers or other devices.

❌ Skip the 27-inch ASRock Phantom Gaming monitor if...

You need lots of pixels for large timelines, detailed layouts or several applications side by side. QHD is a useful step above Full HD, but a 4K monitor provides substantially more working space and detail for those kinds of professional creative tasks.

The Catch: What to know before you buy

The quoted 200-nit brightness is the specification I'd pay particular attention to. That's relatively modest, especially if you work in a brightly lit room or want a display primarily for high-brightness HDR content. There's also no built-in webcam or speakers, so you'll need separate hardware if either is important for your workspace.

• Shop all products in Newegg's Labor Day sale

If you're looking for 32GB of DDR5-6000 RAM, you might be tempted by Newegg's Labor Day deal on the 32GB (2 x 16GB) Corsair Vengeance kit for $490 (was $605).

That's a reasonable deal given the list price, but I've found a much cheaper alternative that offers the same capacity and memory speed.

The Patriot Viper Venom RGB kit is $410 at Newegg, a solid $80 cheaper. For your money, you get two 16GB DDR5-6000 modules with CL36 timings, Intel XMP 3.0 and AMD EXPO support, aluminum heat spreaders and customizable RGB lighting.

Why we recommend it

The Patriot kit supports both Intel XMP 3.0 and AMD EXPO profiles, making it easier to configure its rated memory settings on compatible Intel and AMD systems.

You also get an aluminum heat spreader, thermal sensor and RGB lighting that can synchronize with compatible Asus, ASRock, MSI and Gigabyte motherboards.

Patriot provides its own Viper Venom RGB software as another option for controlling the lighting.

Price context & historical value

Viper Venom's $2 reduction from $411.99 to $409.99 isn't much of a Labor Day discount on its own, so I wouldn't buy this kit because of the sale label.

The value comes when you compare it with the Corsair Vengeance alternative (I've detailed that right here). Even after applying Newegg's coupon to bring that kit down from $604.99 to $489.99, you're still paying $80 more than you would for the Patriot RAM.

Should you buy it?

✅ Buy the Patriot Viper Venom RGB DDR5 kit if...

You want 32GB of fast DDR5 memory and don't see a good reason to spend another $80 on the Corsair kit. Both give you 32GB across two 16GB modules running at DDR5-6000, making Patriot the much cheaper route to the same capacity and rated speed.

❌ Skip the Patriot Viper Venom RGB DDR5 kit if...

You want the tighter memory timings offered by the Corsair Vengeance kit. Patriot's RAM is rated at CL36 with 36-36-36-76 timings, whereas the Corsair alternative runs at CL30, so the extra money does buy you lower latency.

The Catch: What to know before you buy

Compatibility is the important limitation here. Newegg specifically states that the Viper Venom kit isn't compatible with Intel Core Ultra Arrow Lake processors, so don't buy it for a newer Intel system without checking your motherboard and CPU compatibility first.

For supported systems, Patriot lists compatibility with AMD 600 and 800 Series platforms alongside Intel 600 and 700 Series motherboards, including Z690 and Z790.

• Shop all products in Newegg's Labor Day sale

• Lenovo showed Project Swan at IFA 2026, a concept notebook whose 14-inch display rolls out horizontally to a 17-inch 16:9 panel, at 17.9mm and 1.6kg
• It is 90g lighter and 2mm thinner than the vertical ThinkBook Plus Gen 6 Rollable that Lenovo already sells, pointing to a maturing lineup from the computer giant
• It has a compelling business case for people who currently carry a portable monitor for work, but given the current model's pricing, it may come at a significant premium versus the solution it competes with

Lenovo showcased Project Swan at Innovation World during IFA 2026, a proof-of-concept notebook that functions as a 14-inch machine in its compact form and expands into a larger 17-inch 16:9 display when more space is needed.

The laptop measures 17.9mm thick and weighs 1.6kg, and targets customers who do a lot of multitasking, side-by-side document review, presentations, dashboards, and creative workflows.

The model currently has no price tag, no ship date, and no named processor, beyond the company's statement that both concepts, including the fanless AeroBlade, will be powered by Intel at launch this year.

Pitched at users leveraging a portable monitor with a large budget in tow?

Lenovo's Project Swan isn't exactly a new product offering, but an improvement on something the same company already offers. Lenovo already sells its sibling, the ThinkBook Plus Gen 6 Rollable, which went on sale in June 2025 and does the same trick vertically by expanding a 14-inch panel to 16.7 inches, costing at least $3,300 at launch.

Comparing that relatively astronomical price tag to a traditional 14-inch laptop that could cost as little as $1000 from the same company and a portable monitor starting at $200 makes for a very daunting comparison, especially for business buyers, where it could make the difference between a fleet purchase and a niche buy for executives.

It does have some upgrades in thickness and weight over the Gen 6, however: the Gen 6 Rollable is 1.69kg in a chassis 19.9mm thick, while Project Swan is 1.6kg at 17.9mm, shaving off both 90 grams of weight and 2mm of thickness, signaling a maturing technology versus an actual ground-breaking product.

The larger screen and the mechanism to roll it does come with a penalty, however; the ThinkBook 14 Gen 9 announced in parallel with it is 1.3kg at 17.7mm of thickness, beating it soundly in the former and slightly in the latter metric. Against Project Aeroblade, which clocks in at 830g, the weight difference is nearly twice that of the fanless design that Lenovo can currently produce.

The people who benefit are those who need two documents open simultaneously and cannot rely on a second screen being where they are going: contract reviewers, auditors on client sites, translators, analysts comparing a model against its source, consultants presenting across a table without a projector.

For that target audience, the alternative today is carrying a portable USB-C monitor, and the weight calculus favors Project Swan tremendously: A 15-inch portable monitor typically runs 700 to 900 grams, and a comparable 1.3kg ThinkBook plus a screen is around 2.1kg in the bag against the Swan's 1.6kg, with no secondary cable to manage.

Whether Project Swan arrives at an acceptable price point determines whether the rollable laptop becomes more than a pricey proof of concept or a viable solution for many users who need a large screen with portability and weight constraints in tow. For now, Lenovo's impressive offering points to an evolution, not a revolution, in a segment that has drawn a lot of interest but little corporate purchase intent because of concerns about price, durability, and repairability, making it a fringe purchase at best for most.

Following the aftermath of the Manchester Airports Group cyberattack - where hackers made off with the data of 8.7 million people - the hackers have now posted the entire database for sale on the dark web.

The group behind the attack, FulcrumSec, attempted to get Manchester Airports Group (MAG) to pay for the security of the database, promising that it wouldn’t be released if the company paid a settlement. But as all companies should do when faced with extortion, MAG didn’t play ball.

Now FulcrumSec wants to try and maximise the damage of the cyberattack, and has listed the database containing email addresses, phone numbers, vehicle registrations and postcodes online in the hopes a fellow hacking group will find value in the data.

What happens when extortion fails, and why didn’t MAG pay?

In the past, when companies faced ransomware attacks or data breaches, they would sometimes quietly pay the hackers for their silence.

Companies feared serious reputational harm and loss of business would cost more in the long run than the perpetrators were asking for. But this created an incentive for hackers to carry out more attacks.

After all, if companies aren’t kicking up a fuss about being hacked or reporting the attack to the authorities, hacking groups can launch more attacks on other companies that are completely unaware of their tactics.

In order to counter this, authorities and cyber experts from around the world issued guidance that under no circumstances should companies pay for the safe return of their data. By removing the incentive from ransomware attacks and data breaches, the hope is that hackers will get bored or not see enough ROI, and therefore stop.

But the 500GB database of data on over 8.7 million people is ripe pickings for other cybercriminals looking to launch highly specific phishing attacks or scam campaigns. While FulcrumSec may not make any money from the attack, they can seriously enhance the damage of the attack by offering the data for free for others to use.

A successful scam or phishing attack can steal banking and financial details, allowing other groups to steal even more money off the back of the attack.

Expert perspectives on MAG extortion and customer data

• Dray Agha, senior manager of security operations at Huntress:

While Manchester Airports Group followed official guidance by refusing to pay the ransom, the release of 8.7 million records creates an immediate risk for passengers.

We expect other criminals to use this freely available database of vehicle registrations, postcodes and contact details to craft highly convincing phishing attacks.

Anyone who has used parking, lounges or Wi-Fi at these airports must treat unexpected messages about their travel with extreme caution.

• Muhammad Yahya Patel, vCISO and cybersecurity advisor for EMEA at Huntress

The "free release" model is deliberately designed to maximise harm and reputational damage as a warning to the next target.

Publishing almost nine million records for free isn't just punishment for MAG it's a marketing campaign aimed at every other organisation watching.

Pay up, or your customers' data gets handed to every fraudster and scammer on the internet at no cost. Refusing to pay a ransom is the right call. But nearly nine million people are now paying a different price for a decision that was never theirs to make.

• Danny Jenkins, Co Founder & CEO at ThreatLocker

Unfortunately, once data is made public, it can’t be hidden again. The most important thing consumers can do is focus on basic cyber hygiene. Use a unique password for every website, learn how to identify phishing scams, and monitor your credit report.

Be highly suspicious of emails that create a sense of urgency, offer something that seems too good to be true, or ask you to reset your password.

When in doubt, look up the phone number for the alleged sender yourself, rather than using a number provided in the email, and call to confirm whether the communication is genuine.

• Brian Higgins, security specialist at Comparitech:

Whilst the airports breached in this attack don't appear to have had any financial data compromised the risk to affected or associated customers is very real. With so much other information freely available in the wild it is vital that airport users stay highly vigilant for some time to come.

Any and all unsolicited contact; whether online, by telephone or even home visit approaches, should be viewed as suspicious. Never engage until you've taken time to check credentials/veracity etc.

Research advice from trusted sources like the NCA or Information Commissioner and share it with your family and friends. Look for ways to increase digital and physical security like two factor authentication on Apps and devices or Smart Home tech.

When this breach was first reported by the Manchester Evening News the comments were quite telling. Affected parties were quick to identify potential vulnerabilities over and above the breach of financial and banking details.

Home addresses, vehicle registrations and time spent away from home all add up to some excellent opportunities for criminal exploitation, not to mention the usual follow-up phishing campaigns common in this type of incident.

As AI makes data aggregation swift and easy consumers are waking up to the fact that criminals can monetise successful breaches in increasingly inventive ways. It’s no longer enough for data owning organisations to advise post-attack vigilance and turn to their backups.

Victim communities rightly expect better protected networks and systems over and above established norms. As the marketplace grows less fearful and more angry when breaches are made public we may see more emphasis on cyber crime prevention which can only be a good thing.

• Denis Calderone, CTO at Suzu Labs:

The 8.7 million number is attention-grabbing, but it deserves some context. MAG has confirmed that the vast majority of those records are email addresses collected through airport WiFi sign-ups.

A much smaller subset includes phone numbers, vehicle registrations, and postcodes from customers who actually completed parking or lounge bookings.

No payment data, no passwords, no passport information. So despite this affecting airports, which is obviously a sensitive subject, the actual data sensitivity for most affected individuals is relatively low.

What's more interesting to us from a technical standpoint is the attack path. MAG told The Register that attackers compromised one of their internal systems and then went on to steal files from a database hosted by a third party. That's a pivot upstream into a data provider, not downstream into operational systems.

What remains unclear is whether the data was exfiltrated directly from that third-party environment or whether it was pulled back through MAG's network first. That distinction matters for understanding where detection controls failed and who was responsible for monitoring the egress.

The UK's Civil Aviation Authority has a Cyber Assessment Framework for Aviation, developed with the NCSC, that mandates strict separation between IT systems and operational technology.

We don't know whether MAG was formally operating under that framework at the time of this incident, but I would be very interested to find out. Because the segmentation appears to have held here. Flight operations, baggage handling, terminal systems, etc., all were unaffected.

The lateral movement went upstream toward a data provider, not downstream toward the systems that keep planes in the air.

• Seemant Sehgal, CEO and Founder at BreachLock:

This data was initially collected because passengers needed a login, and somewhere along the way, the sensitivity of what was accumulating in that database stopped getting the same scrutiny as the network itself.

Vehicle registration details, postcodes, and contact information across three major airports are a profiling dataset, and whoever held it for ransom understood its value better than the organization storing it did.

• Cisco patched eight IOS XR flaws, including three critical (CVE‑2026‑20274, CVE‑2026‑20279, CVE‑2026‑20212)
• Vulnerabilities allow unauthenticated exploitation, improper access control, and crafted input execution
• No abuse reported; patches urged, with iACL workarounds for Nexus 9000 devices using Silicon One ASIC

Cisco patched eight vulnerabilities affecting its IOS XR operating system, including three critical-severity ones. It urged its customers to apply the patches as soon as possible, even though it stressed that there is no evidence any of these were abused in the wild.

The company detailed its findings in two advisories published on the same day - September 2.

In the first one, it disclosed seven vulnerabilities, including two critical-severity ones: CVE-2026-20274 and CVE-2026-20279. Both carry a severity rating of 9.8/10 (critical). The former is an improper control of a resource during its lifetime flaw - a network-based, low complexity, vulnerability that requires no authentication or user interaction to be exploited. The latter is described as an improper access control vulnerability that can lead to the same consequences.

Fixes and mitigations

These flaws, along with five others, affect all releases of Cisco IOS XR Software, including Cisco IOS XR7 (LNT) Software, regardless of device configuration, the company explained. There are no available workarounds, and installing the provided patch is the only way to mitigate the risk.

The third flaw, disclosed in a separate advisory, is tracked as CVE-2026-20212. Successfully exploiting this one allows attackers to connect to an affected device and send crafted input that could be executed as code, without root privileges. “The exploitation of this vulnerability could also cause the S1HAL process to crash, which could cause the device to reload,” Cisco explained.

This bug affects Cisco Nexus 9000 Series Switches if they include a Silicon One ASIC, the company stressed. A possible workaround is to use infrastructure access control lists (iACLs) to allow only required management and control plane traffic that is destined to the affected device. There is also the option of iACLs only being used to explicitly deny all TCP packets that are destined to a locally configured IP address with a destination port of 43210 or 43211.

Via The Register

We've been searching through all this year's Labor Day sales, and one thing is clear: A genuine 4K business monitor for $200 is still a rare find, so this deal really stood out to us. the Samsung ViewFinity S70H is down to $200 (was $300) at Amazon.

This 27-inch 4K UHD monitor has an IPS panel, HDR10, and Samsung's built-in eye-comfort features. Whether you're upgrading a home office setup or adding a second display for multitasking, this is the most compelling Labor Day monitor deals we've seen yet.

Why we recommend it

4K UHD resolution at this price point is still uncommon, and the extra pixel density makes a real difference for text sharpness and general productivity compared to a standard 1080p or 1440p display. The IPS panel and 178-degree viewing angle also mean consistent color and brightness even if you're not sitting dead center.

HDR10 support and Samsung's Eye Saver Mode, which reduces blue light and prevents flicker, make this a comfortable choice for anyone spending long hours in front of a screen. Samsung's Display Manager software adds useful extras like split-screen layouts and brightness presets without needing third-party tools.

With both HDMI and DisplayPort inputs, it's flexible enough to pair with a laptop, desktop, or games console without needing an adapter.

Price Context & Historical Value

This is the lowest ever price for this Samsung monitor, according to CamelCamelCamel. A $100 drop from $299.99 to $199.99 is a genuine markdown, around 33 percent off, and a strong price for a 4K monitor with HDR10 and IPS color accuracy.

Monitor pricing can fluctuate around major sales events, so it's worth confirming the price is still live at checkout, but this is a solid entry point into 4K at home if you've been waiting for the right price.

Should you buy it?

✅ Buy the Samsung ViewFinity S70H if...

You want a genuine 4K monitor for work or media at a budget-friendly price, you want HDR10 support and Samsung's Eye Saver mode for long screen sessions, or you need both HDMI and DisplayPort inputs for a flexible desk setup.

❌ Skip the Samsung ViewFinity S70H if...

You want a high refresh rate for gaming, since this is a 60Hz panel, you need USB-C connectivity or a built-in KVM switch, or you're after a larger screen than 27 inches.

The Catch: What to know before you buy

This 4K monitor has a 60Hz panel. That's ideal for general office tasks, but it's not built for high-frame-rate gaming. It also skips USB-C connectivity and a built-in KVM switch, both of which appear on some pricier ViewFinity models. For everyday productivity and media use, none of that should matter much.

• Shop the full Labor Day sale at Amazon

• GPT-6 Astra just scored 92.7% on understanding how to interact with your apps, up from 5.6's 76.9%
• New recurrent depth reasoning also allows Astra to think about your problem in a new way
• OpenAI admits there are some safety concerns about how GPT-6 reasons

OpenAI has lifted the wraps off its next-generation model, GPT-6 Astra, and it's being positioned as much more than a conventional chatbot. With this new generation, OpenAI wants us to see its models as being much more suited to computer use.

Being able to fill out forms, update CRM records and organize calendars are among the examples cited by OpenAI, which is especially noteworthy for business customers because it positions Astra as an overarching model that's platform agnostic.

In other words, businesses won't necessarily need bespoke AI APIs or connectors to automate parts of their workflows, because Astra's computer use skill should be able to handle many tasks natively.

GPT-6 Astra could be OpenAI's best business model yet

With its new model, OpenAI is claiming a substantial speed improvement. On the OSWorld 2.0 benchmark, GPT-6 scored 72.6% compared with GPT-5.6's 65.7% and Claude Opus 5's 70.2%. The company's latency simulations put the average task at roughly 40 minutes instead of 75 minutes, marking a near-50% reduction in time.

Astra also scored an impressive 92.7% on ScreenSpot-Pro, which tests a model's ability to understand where to interact with interfaces. GPT-5.6 Sol scored 76.9%, and Claude Fable 5 scored 87.3%.

Among the headline use cases cited by OpenAI in its release information included Astra being able to fully interact with and manipulate Excel spreadsheets, rather than just generating formulas and dumb CSVs, as well as working directly within Power BI to build and refine dashboards, significantly cutting the time a worker could have to spend turning raw data into a presentable format.

GPT-6 also introduces a new reasoning architecture called recurrent depth which allows it to think about a problem repeatedly before producing an answer, which could improve accuracy in high-stakes situations for enterprises.

However, OpenAI admits that monitoring Astra's reasoning has been harder than monitoring Sol's conventional chain-of-thought reasoning, raising some safety concerns, so it's only being rolled out gradually and monitored for now.

Astra is rolling out to Plus, Pro, Business and Enterprise users now, with a Pro variant available to Pro and above. For now, it looks like Free and Go subscribers aren't getting access to the flagship model.

• OpenAI launched Daybreak for Frontline Defenders, offering $1B in credits for resource‑constrained security orgs
• Priority goes to essential services, governments, banks, nonprofits, and open‑source maintainers
• Initiative includes training, partnerships, and a water‑sector pilot with MS‑ISCA for local defenders

OpenAI is offering a billion dollars in credits to security organizations who want to use its Daybreak initiative but cannot afford it.

Daybreak is a cybersecurity program that provides vetted defenders with specialized AI tools and models. It was introduced in May this year, and later expanded into two tiers - Blue, and Red. Blue is the entry-level tier, providing a general-purpose model with custom-tailored safeguards. Red, on the other hand, offers a more purpose-trained cybersecurity model and almost no safeguards.

According to OpenAI, “thousands of defenders across 2,000 approved organizations and workspaces” already use Daybreak, including cybersecurity companies, defense organizations, and law enforcement agencies.

Who gets priority?

But these models cost money, and to make sure more businesses can access them, OpenAI announced, “Daybreak for Frontline Defenders”, a project where defenders can apply and receive credits for AI tokens. Even though the company announced it as a global initiative, it seems that US businesses will be the first to take advantage of it:

“OpenAI is committing $1 billion in subsidized Daybreak access to help resource-constrained cyber defenders, starting with the United States, put frontier AI to work, targeting it to be consumed over the next six months,” the company said in an announcement blog.

Businesses operating essential services such as water and wastewater systems, and electric grid operators, will get priority, OpenAI said. Then come state and local governments, community and regional banks, nonprofits, open-source maintainers, and then “other organizations with limited security resources.”

The subsidy is not just about using the models, though. OpenAI also said it will be increasing hands-on support for frontline defenders, training, and new partnerships.

On top of all that, OpenAI also announced a public sector, water-focused pilot with the Multi-State Information Sharing and Analysis Center (MS-ISCA) to train and support local, tribal, and territorial defenders.

“The pilot will pair Daybreak access with guided training and hands-on assistance for an initial group of public sector and water system defenders, helping them validate and prioritize findings, coordinate remediation, and develop a repeatable approach that can be expanded over time,” the announcement concluded.

• Gemini Audio models power the latest conversational AI in Google Workspace
• Gmail Live can find information buried inside your emails for you
• Users can create Docs and Keep notes with just a brain dump

Google has finally launched the conversational voice features it previewed earlier this May, allowing users to interact with Workspace apps like Gmail and Google Docs by speaking instead of typing.

Much more than just simple dictation, the Gemini Audio models should be able to interpret user intent and retrieve the relevant information.

From launch, the company is supporting its new 'Live' functionality across Gmail, Docs and Keep, but we can expect a fuller rollout as Google continues to tweak the technology based on user feedback and real-world use cases.

Gemini now handles some of your documents and work by voice

Starting with Gmail Live, users can ask things like what gate a flight departs from or what's happening at a child's school during the week, and the model should be able to read and retrieve the necessary information without the user ever having to find the email.

For Docs Live, it's more about generating documents through natural language prompts. Google gave an example of a user giving a 'brain dump' to Gemini, which then goes on to organize the thoughts and produce a structured draft. The tool can also draw information from other Workspace apps like Google Drive, Gmail and the internet.

Keep Live offers similar functionality, turning speech into organized notes rather than simply transcribing a user's thoughts word-for-word.

Google AI Plus, Pro and Ultra subscribers get first access to Gmail Live and Keep Live, beginning now. Docs Live is limited to Pro and Ultra subscribers, cutting access for Plus members. Business customers are also set to get the updates soon.

"Whether searching your inbox, organizing your thoughts, or brainstorming, the new capabilities in Gmail, Docs, and Keep let you do it all conversationally," Google Workspace Product VP Yulie Kwon Kim summarized.

• Hostinger has upgraded its Kodee AI agent
• The tool aims to solve AI fragmentation for small businesses
• It will now reach beyond support, allowing users to create, plan, automate, and analyze work

Hostinger’s AI agent Kodee reportedly solves 91% of 1.5 million support conversations a month, all on its own – a feat so impressive that Hostinger has now given it a new role.

Released earlier this week as Hostinger Agent, the AI agent will now reach beyond support, combining specialized agents that can create, plan, automate, and analyze work.

Hostinger Agent retains the Kodee approach, aiming to solve as many tasks and issues on its own, but handing cases off to human specialists when it is unable to do the job.

AI fragmentation for small businesses

According to a press release shared with TechRadar Pro earlier this week, Hostinger Agent aims to solve the issues of AI fragmentation for small businesses.

Today, many small businesses deal with bots for every vendor, plus their own SEO tool, writing copilot, and analytics agent. Each requires time to set up and get familiar with. Plus, they have no knowledge of the others, often leading to repetitive conversations.

Research by Gartner predicts that 60% of brands will be using agentic AI across key business areas, including marketing, sales, and support, by 2028 - highlighting just how AI fragmentation could compound in the coming years.

“The AI industry has spent the past two years giving people more assistants, copilots, and agents to choose from. We want customers to stop choosing between them,” said Emilis Strimaitis, Head of Product Innovation at Hostinger.

“When the AI already knows what the customer is building and what they are trying to achieve, fixing the immediate problem is only part of the job. The real value is helping them grow online.”

From advice to action

Hostinger Agent solves this by connecting support, marketing, SEO, content and visuals, analysis, and recurring tasks into one interface, letting users launch and manage their website in one space.

The AI agent doesn’t just offer advice; it takes action across your website and within hPanel, reducing the technical know-how and time typically required. By consolidating all of these into one place, it will also be able to develop a better contextual understanding of your business, supporting better advice.

Users will also be able to access Hostinger Agent within AI Builder, Hostinger’s dedicated space for creating websites, stores, apps, and other online projects with AI agents, opening the door for users to build websites and consult with the AI agent at the same time.

Lenovo has consistently impressed us with its line of laptops for business and back-to-school users. And the positively versatile Yoga range is no different. Now, in the Labor Day sale, the Lenovo Yoga 7i 2-in-1 is down to $750 (was $1200) at Best Buy.

This 2-in-1 laptop lets you switch between laptop, tablet, and presentation modes just by flipping the screen. But what I especially like are the specs, which sees the laptop pair Intel's latest Core Ultra 7 processor with 16GB of memory and 512GB SSD.

For students, professionals, or anyone who wants one machine that handles note-taking, streaming, and everyday productivity, this configuration offers a lot of laptop for well under $800.

Why we recommend it

Intel's Core Ultra 7 Series 2 processor brings a genuine step up in everyday performance and a dedicated NPU for Copilot+ features like improved Windows search and on-device AI tools, all while keeping the fanless-feeling thermals reasonable for a convertible chassis.

The 360-degree hinge is the real selling point here. Being able to fold the Yoga 7i into tent, stand, or tablet mode makes it genuinely useful for presentations, sketching, or media consumption in a way a traditional clamshell can't match, and 16GB of memory with a 512GB SSD covers most everyday workloads comfortably.

It's worth noting upfront that outside reviews of this generation have flagged the standard IPS display as dim and lacking in color gamut compared to the optional OLED panel Lenovo also offers on this line. For everyday browsing, video calls, and office work that's rarely a dealbreaker, but it's worth knowing if visual quality is a priority for you.

Price Context & Historical Value

A $450 drop from $1,199.99 to $749.99 is a substantial discount, around 38 percent off, and a genuinely strong price for a 16-inch Copilot+ PC with this processor and memory configuration.

Should you buy it?

✅ Buy the Lenovo Yoga 7i 2-in-1 if...

You want a large 16-inch 2-in-1 for note-taking, presentations, or tablet mode, you want Copilot+ AI features and solid everyday performance from Intel's latest Core Ultra chip, or you need a versatile hinge and long battery life for working in different postures.

❌ Skip the Lenovo Yoga 7i 2-in-1 if...

You need vibrant, color-accurate visuals for photo or video editing, since reviewers have flagged this base IPS panel as dim and narrow-gamut, you're set on the sharper OLED display option instead, or you want dedicated graphics for gaming or heavy creative work.

The Catch: What to know before you buy

The standard IPS display is probably the laptop's biggest weakness, with a low color gamut compared to the optional OLED version. If display quality matters more to you than price, it's worth weighing that trade-off before buying.

• Shop all laptop deals at Best Buy.

Chips from Taiwan, oil from the Persian Gulf, and cars from Germany – what was long taken for granted is now being called into question all over the world. Where markets and expertise are concentrated among a few providers, enormous economies of scale arise.

At the same time, however, dependencies also grow – often with risks that only become apparent when supplies fail, prices rise, demand evolves, policies change, or individual players begin to monopolize the market.

Take AI, for example – according to research institute, Epoch AI, only two notable AI models have emerged in Europe over the past twenty years compared to 50 in the US and 30 in China. The technology has moved so quickly that the repercussions of this imbalance are only just beginning to be felt in European markets.

Is Europe becoming too dependent?

From office applications to storage and computing resources to software, what providers deliver from their data centers in a highly scalable, maximally available, and extremely innovative manner does not, in most cases, originate from the European continent.

According to Bitkom’s Cloud Report 2026, roughly 85% of German companies consider Germany to be too dependent on US providers, and almost two thirds of local users (64%) feel compelled to review their own IT strategy due to US government policy. Countries like France are already taking action, with the French government announcing plans to replace Windows with Linux on its government computers.

At the same time, the national health insurance fund has already migrated 80,000 employees from Microsoft Teams, Zoom, and Dropbox to its own alternatives.

Whether in Germany or France, the question of how digitally dependent companies, governments, and societies are on individual suppliers is being asked throughout Europe. And it has been for some time. While Gaia-X focused on common standards for sovereign cloud computing, the EU is now pursuing a more pragmatic approach.

The Cloud Sovereignty Framework (CSF), unveiled in October 2025, aims to make digital sovereignty measurable. To achieve this, it builds on initiatives such as Gaia-X as well as regulations like DORA and NIS2, with the ultimate goal of being able to prioritize compliant, low-risk providers in public procurement.

The sovereignty metric score

Controlling and regionally consolidating one’s own digital traffic flows. That’s quite a task in a world where AI superpowers are evolving overseas. With regard to IT supply chains, the framework favors providers who operate their environments in a transparent, resilient, and sufficiently sovereign manner to ensure that systems are protected from external influences or the interests of third parties.

This means, for example, that data paths must be traceable and controllable at the regional level to ensure they remain within the EU legal framework. In other words, there is no sovereign cloud without an interconnection strategy. After all, Internet Exchanges (IXs) already play a key role when it comes to processing bits and bytes locally. Wherever companies, networks, and clouds connect at IXs, they exchange information along paths that can be precisely defined geographically.

Although the EU does not explicitly make IXs a scoring criterion, it’s heavily implied. For example, the CSF also evaluates cloud services based on supply chain-related legal, operational, and technological objectives. This concept is also reflected in the NIS2 Directive and argues in favor of more decentralized and resilient backbones, such as mutually secured interconnection platforms, such as IXs.

In practical terms, this means that any IT landscape is only as secure as the individual elements that comprise it. So, if all partners design the components they provide to others with multiple layers of redundancy, the overall system becomes not only more reliable but also more independent for everyone.

Distributed and provider-neutral IXs have already made this principle their guiding philosophy: to allow data to be exchanged with high availability, security, and control – between all companies, partners, and clouds within the digital ecosystem.

Europe at a crossroads

Technical issues can usually be resolved easily, but legal ones often cannot. Therefore, the CSF is unlikely to revolutionize the European cloud market overnight, but it can steer public demand in a targeted manner. As a result, hybrid, multi-cloud, and on-premises approaches are becoming more important, and IT is becoming infinitely more complex.

While unravelling this complexity will take additional effort, the pay-off of rearchitecting networks around neutral IXs will be a two for one: not only will it reduce long-term lock-in risks but will also reduce the threat of having to pay significantly higher prices later on when things inevitably change. Europe must now consciously accept this and align and strengthen its own provider market accordingly.

Just as operations would come to a standstill for 46% of companies in a prolonged outage, without the cloud, there can be no functional public administration – and no independent, sovereign, and thus capable state.

We've featured the best cloud storage.

This article was produced as part of TechRadar Pro Perspectives, our channel to feature the best and brightest minds in the technology industry today.

The views expressed here are those of the author and are not necessarily those of TechRadarPro or Future plc. If you are interested in contributing find out more here: https://www.techradar.com/pro/perspectives-how-to-submit

When businesses and governments delegate operational tasks to AI agents, the discussion tends to start with capability. Can AI do what a person can do, such as reconcile accounts, negotiate with suppliers, sign a document or submit a public filing? And can it do so quickly and cheaply enough to justify putting it to work?

These questions matter, but performance is only part of the picture. Once an agent acts independently, different questions emerge; who authorized it, whose interests does it represent, where does its authority end and, perhaps most importantly, who is responsible when something goes wrong?

This is the accountability gap in agentic AI, and a more advanced model will not close it. An agent might be remarkably capable, yet still act with potentially unwanted or possibly even unlawful consequences.

The only way to bridge that gap is through a system with clear permission guardrails and an audit trail that links each agentic action to the person that authorized it, and can tell the difference between a person and a machine in the first place.

Ordinary error at extraordinary scale

When people think about AI risk, they tend to picture a machine breaking free of human control and pursuing goals of its own. The more immediate risk is less dramatic; a system simply getting an ordinary task wrong, again and again, with no clear line of responsibility and accountability.

A person might send an invoice to the wrong customer. An agent connected to the full customer database could send the same invoice to thousands. It might change the wrong field and then repeat the change across an entire market, not because it has become malicious, but because it has misunderstood an instruction and had the access to act on that.

The speed that makes an agent valuable can save a business hundreds of hours, but can also turn a small and recoverable mistake into a serious operational problem.

When an agent drafts an email for someone to review, this ambiguity may not matter very much because the person remains between the software and the outside world.

But when it can send the message, submit a declaration or move money, it matters a great deal. Imagine asking an assistant to book one flight and, instead of giving them a company card with an appropriate spending limit, handing over your passport, bank card and office keys. You may trust the assistant completely, but the permissions bear no sensible relation to the task.

Define the boundaries, solve the problem

AI agents cannot hold citizenship or legal personhood, but they can be linked to natural persons in legally sound ways. For example, a reliable identifier could trace the agent's activity back to the person responsible for deploying it. Combined with clear permissions and mandates that make the terms of its authority visible and auditable, this would allow AI agents to carry out a range of operations and transactions in a more controlled way.

These controls could be very precise. An agent might be allowed to view financial information but not change it, prepare a payment but not approve it or order from named suppliers without exceeding a fixed amount. Its permissions might last for one transaction, one working day or the duration of a particular contract, after which it would expire without relying on someone to remember to switch it off.

Withdrawing that authority should be equally straightforward. If a company ends its relationship with an agent, changes supplier, or discovers that something is wrong, it should be able to cancel the it’s access without changing the credentials of the person behind it.

The agent’s legally anchored mandate in the various realms of these controls has a longer shelf life than any individual AI model, which will be upgraded, replaced and combined over time, often without the customer seeing much more than a new version number.

Putting the idea into practice

Estonia has decided to work through these questions now. In June, the government began developing a state-backed registration system for AI agents that will be available to both Estonian citizens and the country’s global community of entrepreneurs. The goal is to explore how Estonia’s fully digital state, where all public services are available online, can be opened to the emerging wave of AI-powered businesses.

Under the current proposal, a person would receive a registered numeric identifier that could be linked to one or more agents acting on their behalf. Operations performed by an AI agent are treated as operations performed by a machine, for which the natural person, the identity anchor, is liable. The AI agent can only operate within the limits of the authorizations granted to it.

For transparency, private service providers also need to know whether an operation was performed by a person or by a machine acting on their behalf. This allows them to apply appropriate controls, restrictions and risk models.

Built for delegation

The approach draws on more than two decades of digital government. Estonia’s system of personal identifiers and digital identities already allows people to act on behalf of others with clearly defined permissions.

An accountant can file a client’s taxes, an adult can manage an elderly parent’s affairs through the health portal, and several people can use a corporate bank account with individual rights and limits. In principle, the same framework could support mandates for AI agents.

This would give users greater confidence that safeguards are in place to protect the responsible person from foreseeable errors by an AI agent. It would also help close the accountability gap as agentic activity increases.

Before AI agents are given executive powers, they need a technically and legally binding framework that records who they represent, what they can do and who remains responsible for their actions.

We've featured the best AI tool.

This article was produced as part of TechRadar Pro Perspectives, our channel to feature the best and brightest minds in the technology industry today.

The views expressed here are those of the author and are not necessarily those of TechRadarPro or Future plc. If you are interested in contributing find out more here: https://www.techradar.com/pro/perspectives-how-to-submit

• Tottenham Hotspur just confirmed plans to migrate from VMware to HPE, saving 85% off its bill
• CTO Rob Pickering revealed that Broadcom-era changes are largely to blame
• The stadium is also undergoing a broader HPE upgrade

Tottenham Hotspur has phased out VMware at its stadium as part of a major infrastructure overhaul. By moving to HPE Morpheus VM Essentials, the London football team managed to cut virtualization costs by more than 85%.

According to Ars Technica, CTO Rob Pickering explicitly pointed toward the commercial changes following Broadcom's acquisition of VMware.

But for Tottenham, the migration was just one part of a major data center and networking refresh, with the company also shifting its server, storage and networking infrastructure – incidentally, to HPE.

Tottenham moves from VMware to HPE, saves 85%

Though the team didn't reveal how much it paid for which products with VMware, Pickering did say the saving was a "significant amount" and "north of 85%."

"The issues with the Broadcom takeover of VMware are well-known in terms of the commercial changes to their structure and the way that they engage with clients," he added.

Tottenham also confirmed that integrating virtualization, infrastructure and automation into one single operational stack ultimately led to more value than simply swapping one virtualization vendor for another to save money, hence the decision to go all-in on HPE.

Earlier this summer, HPE announced that it would be offering prospective customers a year's free HPE Morpheus VM Essentials for customers switching from VMware to help ease the cost involved with migration. Its Zerto migration software was also confirmed to be part of a $1 package.

It's unclear whether Tottenham Hotspur took advantage of those offers.

At the same time, the stadium is also said to have started a major network upgrade toward Wi-Fi 7 and HPE Aruba Central in a stadium with around 20,000 network access points and connections.

More broadly, Tottenham Hotspur isn't the only business turning its back on VMware – UK supermarket giant Tesco also confirmed plans to dump 40,000 VMware licenses.

With the memory crisis continuing, we're always on the look out for DDR5 RAM deals like this TeamGroup T-Force Delta 64GB DDR5-6000 memory kit, which is down to $820 (was $870) at Newegg with code LDSF244.

With TUF Gaming-certified RGB styling, this capacity is built for creators, streamers, and professionals simultaneously running several demanding applications across Intel 700/800 series and AMD 600/800 series platforms.

Why we recommend it

DDR5-6000 sits in a good sweet spot for current AMD and Intel platforms, fast enough to see real gains over stock speeds without needing exotic motherboard tuning. CL38 timings are respectable for a kit at this speed, and Team Group backs it with a limited lifetime warranty.

64GB total capacity is well beyond what most everyday PCs need, but it matters for anyone doing video editing, running virtual machines, or keeping dozens of tabs and apps open without slowdown. Buying it as a matched dual-channel kit avoids the compatibility headaches that can come with mixing modules.

The TUF Gaming branding and RGB heat spreaders are a nice touch if your build already leans into that aesthetic, though the kit will work fine on any compatible board regardless of styling.

Price Context & Historical Value

A $50 discount off $869.99 works out to a modest saving in percentage terms, and it only applies with the LDSF244 promo code at checkout rather than automatically. Memory pricing has been volatile over the past year, so a genuine dollar-for-dollar markdown on a 64GB kit is still worth taking seriously if you were already in the market for this capacity.

Should you buy it?

✅ Buy the Team Group T-FORCE Delta RGB TUF Gaming 64GB DDR5-6000 Kit if... you're building or upgrading a high-performance PC and want ample headroom for multitasking, content creation, or gaming, you want RGB styling that matches a TUF Gaming build, or you don't mind entering a promo code at checkout to get the full discount.

❌ Skip the Team Group T-FORCE Delta RGB TUF Gaming 64GB DDR5-6000 Kit if... 64GB is more capacity than your workload needs, your motherboard doesn't support DDR5-6000 speeds, or you'd rather buy at the listed price without tracking down a promo code.

The Catch: What to know before you buy

The price. It's always the price. Driven by hungry AI, the RAMpocalypse has unfairly sent memory costs sky-rocketing for everyone. That means we're all paying more these days for RAM that cost a lot less even a year ago. You'll need to remember to apply promo code LDSF244 at checkout to get the $819.99 price, and Newegg lists this as a limited-time offer, so it could disappear or revert to $869.99 without much notice.

• See all desktop memory at Newegg.

Agentic commerce has cleared its first hurdle, that of consumer demand. ChatGPT handles an estimated 50m shopping queries a day, and AI-referred traffic to US retail sites rose by nearly 400% in the first quarter of 2026. The unresolved question is where that demand settles once a purchase is made. The early evidence points to the scaled, branded marketplace.

According to Similarweb, marketplaces already receive more AI-referred traffic than any other retail category, some 47m visits in the year to May 2026, and continue to grow faster than their scale would predict.

The mechanism is a mutually reinforcing relationship between consumer preference and LLM recommendation, and its logic points towards a concentration of agent-led commerce on large platforms, with material consequences for merchants and their payment suppliers.

The pattern in AI referral traffic

Revealed consumer preference is a much more reliable guide to market development than stated intent, and the traffic data for agentic commerce is gradually building a picture of how consumers actually use agentic commerce rather than just speculation. Similarweb’s recent analysis ranks marketplaces first among retail categories for AI-referred visits, ahead of news, travel and finance.

Two features are notable. The category commands the largest absolute volume of click-through traffic, and it continues to expand at more than 230% a year despite that already substantial base. The explanation lies in how large language models (LLMs) assemble their recommended shortlists.

Faced with an open-ended shopping request, a model favors platforms with broad catalogues, well-structured product data and extensive reviews. Large marketplaces can provide these in abundance by providing a single source that can satisfy the widest range of queries with the strongest supporting evidence.

Testing the democratization thesis

A contrary hypothesis has been influential. Shopify’s president, Harley Finkelstein, has characterized agentic commerce as ‘fundamentally merit-based’, arguing that it would widen discovery to the long tail of smaller merchants rather than reinforce the incumbents that dominate conventional search.

The demand is not in doubt: Shopify reports that AI-referred traffic to its stores has risen roughly eightfold in a year. The distribution of that demand, however, is less even than the thesis implies.

Marketplaces, not independent sellers, are absorbing the largest share of AI referrals, and the agentic platforms attempting broad merchant onboarding have found it difficult. OpenAI has scaled back open instant checkout in favor of a smaller set of curated partners, citing the complexity of onboarding and verifying merchants at scale.

The emerging structure is therefore symbiotic. Marketplaces supply a large, trusted brand within which a long tail of smaller sellers operate. The individual merchant still reaches the agent-guided shopper, but within a brand and trust environment the consumer and the model already recognize.

This arrangement addresses the consumer trust problem that the open web does not, since the platform has verified the seller before the listing appears, and it retains the operational layer, fulfilment, dispute resolution and logistics, that an agent appear unwilling to take responsibility for. The long tail is not excluded so much as commercially enabled by marketplaces.

A self-reinforcing loop

Beneath the traffic figures lies another dynamic that has received relatively little analysis. Consumer preference and algorithmic recommendation reinforce one another. Consumers already trust marketplaces in a traditional ecommerce use case and select them when an agent presents the option.

Learning models, optimized on the recommendations consumers select, are more likely to surface marketplaces more frequently, reinforcing the habit and shaping the next recommendation. Over successive interactions the marketplace becomes both the more probable choice for the shopper and the more probable output of the model.

New international survey of agentic shoppers indicates that these outcomes are already in consumers’ minds. Consumers tell us they are looking for an independent (i.e. non-seller embedded) agent to compile the shortlist, followed by the reassurance of a familiar brand and visible reviews, a combination that large LLM brands and marketplaces are well placed to provide.

The research also showed that 74% of agentic shoppers in the US and Europe favor an independent assistant capable of comparing across sellers, against 10% who prefer one embedded within a single seller. Brand recognition is also important to 89% of respondents, and customer reviews to 93% when deciding which recommendation to pick from an agent’s shortlist. Most significantly, 93% expect to use retail marketplaces as much as or more than before as the adoption of agentic commerce grows.

Why marketplaces hold the advantage

Consumer preference is only part of the explanation. The economics facing the agent point in the same direction, for three reasons.

The first is remuneration. Most large marketplaces operate established affiliate and commission schemes, providing a ready mechanism to reward an agent for delivering a customer. As agents assume the role once played by referral sites and publishers, the marketplace platforms with mature payout infrastructure are the simplest to monetize.

The second is conversion. Marketplaces have invested heavily in low-friction checkout, so an agent compensated on completed sales rather than referrals has reason to direct shoppers where a purchase is most likely to conclude, which compounds the commercial pull towards the platform.

The third is payment. Agentic commerce already leans heavily on credentials held on file. The dominant standard, Google’s Universal Commerce Protocol (UCP), only transacts against tokenized credentials held on file rather than card details entered by hand, and marketplaces already hold card credentials for hundreds of millions of shoppers.

The advantage is not only the agent’s. Agentic commerce is still nascent: technical standards are still emerging, liability and commercial terms are unresolved, and fraud is migrating to the channel. Absorbing that uncertainty requires capital, specialist staff and an appetite for risk.

Large marketplaces can invest through the ambiguity, adopt and switch between emerging protocols, and operate the fraud and dispute controls the channel demands. For most mid-sized and smaller merchants, the same burden is disproportionate to their means and their tolerance for risk, a further reason to participate through a platform rather than to carry the complexity alone.

An acceleration, not a departure

The movement towards marketplaces predates agentic commerce, and there is a long list of large retailers that have already built or joined them. Kingfisher opened a third-party marketplace at B&Q in 2022, and such sales now represent around 40% of B&Q’s online revenues.

Tesco launched Tesco Marketplace in June 2024 and listed more than 300,000 third-party lines within eight months. Target has told investors it intends to expand its invitation-only Target Plus marketplace from more than $1bn to more than $5bn in gross merchandise value within five years. In each case a trusted retail brand hosts a long tail of smaller sellers, the configuration the referral data now rewards.

Implications for merchants and acquirers

The likely consequence is that agentic commerce accelerates this migration, and that the reinforcing loop strengthens rather than dilutes the move towards marketplaces. The effect will likely divide according to the scale and strength of a merchant’s brand.

Larger, well-known retailers may choose to become marketplaces in their own right, hosting third-party sellers beneath their own name, as Kingfisher, Tesco and Target have done.

For smaller merchants the choice is more likely to be additive: most will want to retain a direct presence while also selling through one or more established banners, drawing on the reputation of the host and a position within the recommendation loop.

This is the next stage of a long-standing movement of smaller firms into marketplace distribution rather than a break from it.

Direct commerce will not disappear. Merchants with strong brands, machine-readable reviews and genuine loyalty can still secure the agent’s shortlist independently, and Salesforce reports that retailers operating their own shopping agents have grown sales roughly 60% faster than those without.

For the broad middle of the market, however, and particularly in impersonation-prone categories such as fashion and footwear where consumers and their agents may have concerns about seller trust, a marketplace presence may become a competitive requirement.

For acquirers, the shift accelerates a migration of volume that is already underway by moving spend onto a smaller number of large platforms. Meanwhile the direct-merchant portfolio shrinks and may be exposed to elevated fraud risk as fraudsters exploit the weakest validation layer.

Acquirers with strong exposure to the marketplace segment are well placed, while the rest of the market faces yet another reason to move into the platform economy.

We've featured the best ecommerce hosting.

This article was produced as part of TechRadar Pro Perspectives, our channel to feature the best and brightest minds in the technology industry today.

The views expressed here are those of the author and are not necessarily those of TechRadarPro or Future plc. If you are interested in contributing find out more here: https://www.techradar.com/pro/perspectives-how-to-submit

Most manufacturers didn't need a business case to understand the cost of reactive maintenance. They'd been absorbing it for years – unplanned stops, recovery overtime, expedited parts, the slow erosion of scheduling confidence and customer trust. What shifted was the available answer. AI in maintenance moved from speculative to deployable fast enough that the investment case made itself.

Industry commitment is real, but something isn't converting at the rate anyone projected. Our recent research found that approximately 78% of all reported barriers to progress are workforce-related. Access to AI moved faster than the ability to use it consistently. That gap is now the constraint.

The first wave proved the tools, not the model

Manufacturers are investing in AI to improve productivity, yet many are still carrying the behaviors that predictive maintenance was meant to reduce.

The research shows predictive maintenance adoption has more than doubled year over year, while reactive maintenance remained flat. Proactive maintenance has also lost ground year over year. That combination is the point: new methods are entering the plant, but they’re not fully replacing the old ones.

This shouldn’t be read as failure. Plants moved for practical reasons, and early pilots gave teams useful proof. A model can work well on a known asset with a focused team around it. The harder test comes when that model has to support decisions across shifts, sites, and mixed levels of experience.

That’s where the first wave exposed the next problem. Technology can move quickly into the budget. Work habits, trust, decision rights, and frontline confidence take longer to change.

AI investment grows up

The budget data confirms that leaders aren’t walking away from AI; they’re becoming more selective about where it has to prove itself. Investment is moving away from exploratory AI and toward operational priorities, including cybersecurity, data management, Generative AI and Industrial AI.

That shift reflects a more practical view of digital maturity. Leaders are trying to make AI work where the cost of delay, downtime, and poor data shows up quickly.

It also reframes expectations around Industry 5.0. As industrial technology moves from Industry 4.0’s automation-led model toward a more human-in-the-loop approach, leaders appear to be recalibrating the timeline, with 40% now expecting a one- to four-year journey.

Where the model stops and the supervisor starts

It’s easy to misread the 78% workforce-barrier figure as a labor shortage story – headcount, hiring, pipeline. However, the truth of the matter is that businesses are facing a lack of expertise, knowledge shortages, skilled labor gaps, and broader workforce capability deficits. Taken together, those four categories describe something harder to fix than a recruitment problem. They describe an organization's capacity to absorb a different way of working.

It's a pattern I hear consistently from customers: the tools are in place, but the teams around them are still catching up. Researchers Cohen and Levinthal gave that capacity a name: absorptive capacity.

In plain English, it’s how quickly a business can recognize useful new knowledge, absorb it into the organization and convert it into practical output. In a maintenance context, that output is a decision made under real operating conditions – by a night-shift supervisor weighing whether a current anomaly justifies an intervention, whether it can wait until the next planned stop, or whether the risk has already crossed a line. A model can flag the anomaly. It can’t make that call.

What predictive maintenance and AI actually demand from the workforce is harder to train than tool proficiency. The UK Government’s AI Skills for the UK Workforce report identifies the gap in concrete terms for advanced manufacturing.

Beyond technical application skills like training AI models or integrating real-time analytics, the report points to the ability to interpret AI outputs, adapt workflows around new insights, and communicate changes to frontline teams. These are key competencies that determine whether an alert changes behavior or gets dismissed.

That’s why the workforce issue can’t sit beside the technology program as a separate HR workstream. It’s part of the system that decides whether investment turns into better execution. Industry 5.0’s timetable will be set by capability on the plant floor.

Investing for predictive, paying for reactive

The commercial consequence is visible in the lag between spending and return. Predictive adoption is rising, more capital is being allocated, yet the reactive baseline hasn’t moved. Many plants are running two modes of operation at once – investing for data-driven execution while still losing time to avoidable firefighting.

That split has a cost. Siemens’ 2024 True Cost of Downtime research puts unplanned downtime losses for the world’s 500 biggest companies at $1.4 trillion annually – 11% of their total revenues. That figure reflects what happens when the shift from reactive to predictive is incomplete. The investment is there, but the daily execution hasn’t fully followed.

When that gap persists, ROI on technology spend arrives slowly and unevenly. Timelines extend. Confidence in delivery weakens.

Where the return is earned

The discipline being applied to tools and platforms now needs to apply to the people and routines around them. For many organizations, that’s where the return is being left on the table.

Leaders should start with the parts of the operation where capability is most fragile. Which assets still depend on one or two experienced technicians to interpret what’s happening? Which work histories are too thin to support the next diagnosis? Which alerts trigger confident action, and which sit in limbo until the right person is on shift?

Those questions reveal whether predictive maintenance has become part of execution or whether it’s still sitting on top of reactive habits.

Capture the know-how that still lives in people’s heads before it walks out the door. Make work histories complete enough to help the next technician. Train operators and maintenance teams to understand what a predictive alert is telling them, what evidence warrants action and when to escalate. Shape workflows so acting on insight becomes the normal path, not a special effort.

Connected reliability supports that execution when it stays close to the work – connecting asset data, maintenance history and frontline judgment so teams can make repeatable decisions across shifts and sites.

Our research backs this up: nearly half of respondents plan to advance connected reliability initiatives within the next 12 months, treating reliability as the practical bridge between near-term operational needs and longer-term ambitions.

The call for manufacturing leaders is straightforward: audit capability with the same seriousness as technology spend. Don’t stop at asking what AI has been deployed. Ask who can act on it, where decisions slow down, what knowledge is undocumented and which workflows still pull teams back into reactive work.

We've featured the best AI tool.

This article was produced as part of TechRadar Pro Perspectives, our channel to feature the best and brightest minds in the technology industry today.

The views expressed here are those of the author and are not necessarily those of TechRadarPro or Future plc. If you are interested in contributing find out more here: https://www.techradar.com/pro/perspectives-how-to-submit

• Four federal agencies criticized for failing to share the framework's details
• We don't know anything about who's involved and how models are tested
• Protect Democracy wants a court order by the end of the month

Four separate US federal agencies are being sued over the Trump administration's secret framework for testing frontier AI models before they get released.

Protect Democracy argues that "almost no details" have been shared about how the framework works, who participates in it, how companies are selected or what legal authority underpins the reviews.

The nonprofit warns the secrecy is especially significant because the government could potentially influence which AI models can be released and who can access them.

US government agencies sued over AI framework

This comes after weeks of battle between Claude-maker Anthropic and the US Government following revisions to the availability of Mythos 5 and an attempt by President Trump to blacklist the company.

Protect Democracy wants the government to disclose the framework's details, its participation terms, the identities of participants, rules governing access to frontier models and the contractual arrangements. The group also wants an injunction preventing agencies from withholding records that are not classified.

The government bodies in question include the Office of the National Cyber Director, the Office of Science and Technology Policy, and the Departments of both the Treasury and Commerce.

The White House has argued that aspects of the evaluation legitimately need to remain a secret, and national security-related tests could contain classified information.

"Just because things are unclassified, that doesn’t mean we are going to broadcast them to everyone," a White House spokesperson said.

Protecting Democracy isn't the only entity concerned about the framework. US Representative Greg Casar (D-Tx.) accused Trump of "completely failing to keep us safe from the dangers of AI" and being "too busy cashing in to protect our jobs or national security."

With Congress also in the dark, Protect Democracy argues the details are needed for both congressional oversight and public accountability.

The group is now seeking a court order for disclosure of the non-classified framework and related details by September 30.

• Chinese companies have spent the past four years filling gaps left by US bans
• The number of IPOs centered around semiconductors has increased
• China is also concentrating on supply chain self-sufficiency

New Morgan Stanley data cited in a South China Morning Post report has demonstrated a shift in the companies reaching China's public markets, per the analysis of 229 IPOs on Shanghai's Star Market between 2022 and 2026.

The number of companies targeting China's technological 'chokepoints' has become much more prominent – around one in five of the IPOs fell into this category in 2026, compared with fewer than one in ten in 2022.

In other words, the SCMP claims that the number of companies addressing areas of foreign technological dependence has more than doubled in just four years.

China's public market fills in response to US restrictions

In the four years analyzed, the so-called chokepoints have concentrated around the semiconductor supply chain following US restrictions and sale bans.

But by preventing the sale of some of its own chips and hardware, the US has fundamentally enabled China to grow its own market by giving it an incentive to develop domestic alternatives.

Morgan Stanley identified 21 companies in 2026 that were specifically targeting these shortfall areas – 19 of them were closely aligns with the semiconductor supply chain.

The investment banking giant also estimated that around 60% of the companies listing in 2026 contribute to China's supply-chain self-sufficiency drive, up from 41% in 2022.

While some restrictions have been eased during that time period, China continues to invest heavily in this market, with continued investments across key remaining areas like raw materials and manufacturing machinery.

Ultimately, years of US technology restrictions have increasingly pushed Chinese startups towards replacing that foreign technology, and even if restrictions were to stop overnight, it's likely that China could now be in a position not to need US hardware anymore anyway.

• Microsoft warns of Teams‑based campaign where attackers impersonate IT staff
• Victims tricked into granting remote access, leading to malware, lateral movement, and ransomware
• Defenses: verify support contacts, train staff, harden Teams, and use Defender Safe Links/ZAP

Microsoft is warning about an ongoing hacking campaign that starts with a Teams message and ends with a ransomware infection and data theft.

In a new in-depth report published on the Microsoft blog, it was said that unnamed threat actors were reaching out to their targets at various enterprises via a Teams chat, while impersonating IT staff.

They were coercing their victims into granting remote access via screen sharing or remote monitoring and management tools and once received, used their access to install malware loaders and various other implants.

How to defend against Teams-borne phishing

The malware was just the first stage of the attack. Subsequent stages include host reconnaissance, security-product and virtualization discovery, and “periodic desktop screen capture”. In other words - mapping out the landscape and conducting espionage.

The crooks would then enumerate domain accounts, servers, and users, through native tools and Active Directory Service Interfaces (ADSI) queries and begin moving laterally.

The final step includes identifying and extracting valuable data, followed by a ransomware infection.

Microsoft does not name the perpetrators, and mostly refers to them as “threat actors”. It makes sense, since the “fake IT support via Teams” technique is being used by multiple groups at this moment. Russia’s Cozy Bear, FIN7, and Storm-1811 are probably the most obvious examples.

The world’s biggest extortionists - ShinyHunters - are also known to use Teams to trick victims into granting access, but this group rarely deploys an encryptor and instead just focuses on data exfiltration.

Whoever the attackers are, and whoever they’re after, one thing is for certain - the risk in the enterprise environment has never been greater.

That is why Microsoft advises reinforcing user education by establishing internal helpdesk authentication phrases, and by training employees to recognize external-tenant indicators.

The company also urges enterprises to verify unsolicited support contact, and to harden Microsoft Teams and email against social engineering. “Use Microsoft Defender for Office 365 with Safe Links and Zero-hour auto purge (ZAP) so malicious messages and URLs are neutralized at time of click and removed after delivery,” Microsoft urges.

• Lenovo showed Project AeroBlade at IFA 2026, a fanless 14-inch concept under 10mm thick and under 830g, cooled by a solid-state Active Flow system built with Frore Systems
• Lenovo dubs this a 'quieter, cleaner computing experience' sans the performance tradeoffs that many similar designs have to make
• Published AirJet specifications and Intel's own 11.3mm reference design put sustained cooling near 15 watts, so "full-performance computing" from Lenovo might be a reach at best currently unless its purported breakthrough offers considerably more cooling than the former's already established tech

Among the shipping products at Lenovo Innovation World during IFA 2026 are two proof-of-concept machines, and the more consequential of the two, somewhat ironically, is not the one with the moving screen.

Project AeroBlade is a 14-inch notebook measuring under 10mm thick and weighing under 830g, built from magnesium-aluminum with a high screen-to-body OLED display, Thunderbolt 4, and Wi-Fi 7 that eliminates fans in the process.

Lenovo cools it with what it calls Active Flow, a solid-state thermal architecture developed with Frore Systems and built on top of the latter's AirJet technology.

Big promises, but relatively scant details

Lenovo claims the resulting product delivers full-performance computing and sustained AI performance without the compromises normally associated with fanless designs.

This could depend on what one considers 'full-performance' computing and AI use, as well as the underlying CPU and GPU configuration. Frore Systems' AirJet is not vaporware; it is proven technology that uses a piezoelectric cooling chip to move air with membranes vibrating above the range of human hearing, and the solution has shipped in mini PCs and SSD enclosures for two years.

An AirJet Mini removes 5.25 watts of heat at 21 dBA while drawing up to one watt, in a package 2.8mm thick and weighing nine grams, generating 1,750 pascals of back pressure. A Mini Slim variant trims that to 2.5mm at the same capacity. The higher-capacity AirJet Pro, rated at 10.5 watts, has since been discontinued, so scaling now happens by adding 5.25-watt modules rather than upgrading to a larger unit.

The tech, however, has not been abandoned or ignored, with Intel building a Wildcat Lake laptop reference design around an AirJet Mini wrapped in a vapor chamber, and Tom's Hardware reporting 15 watts of sustained cooling in a chassis 11.3mm thick.

Lenovo's AeroBlade, however, is thinner at just under 10 mm, which would make it a small achievement if it still sustains 15 W of cooling, but it also means Lenovo is being pickier than most when it comes to choosing facts here: it may just be running a low-powered chip at "full-performance".

For context, the ThinkBook 14x Gen 2 Lenovo is shipping from Q1 2027 carries a 25W TDP CPU under the hood, and running that at maximum design power would require a significantly larger cooling mechanism: the equivalent of five AirJet Minis and a vapor chamber to match.

Lenovo's concept does have advantages, however: it will be much quieter than any design that uses fans, while also removing a key component that can cause hardware failures or RMAs, making longevity a key gain for future designs based on the same approach.

For now, however, Lenovo has not attached a price, a date, a processor, or a single executive quote to the proof-of-concept laptop, which effectively means that it is years from becoming a viable mainstream option. It has, however, demonstrated that a 14-inch business laptop under 830 grams with Thunderbolt and no moving parts can be built with components that exist today, and that alone is arguably a sizeable victory for enthusiasts wanting a quiet but powerful x86-based alternative to the passively cooled MacBook Air.

• Lenovo announced the 11th-generation 15" Yoga Pro 9n and 16" Yoga 9n 2-in-1 at IFA 2026, both running NVIDIA's RTX Spark with a 20-core Grace Arm CPU and a 6,144-core Blackwell GPU
• The understated highlight for business users and professionals is the 128GB of unified memory that the Pro 9n offers, essentially allowing for large LLMs to be run on-device
• This is essential for companies that are required not to transmit sensitive data or use cloud APIs for their AI requirements

Lenovo announced two Yoga laptops running NVIDIA RTX Spark at its Innovation World event during IFA 2026, and the spec that may matter most to professional buyers isn't the GPU but the massive maximum memory both offer.

While the Lenovo Yoga 9n is limited to a 16-channel 256-bit 64GB LPDDR5X configuration, the Pro SKU doubles this to 128 GB.

The change allows the Yoga Pro 9n to run large models on-device, an impressive feat for a device that weighs only 1.65kg but houses a capable Blackwell RTX GPU that can muster as many as 6144 cores for local AI needs.

Peaking under the hood of the RTX Spark-powered Yoga laptops

The underlying silicon is NVIDIA's RTX Spark, unveiled on May 31 ahead of GTC Taipei and long rumored under the codename N1X. Both laptops pair a 20-core Grace-class Arm CPU with a Blackwell RTX GPU with 6,144 CUDA cores, roughly comparable to a laptop with a GeForce RTX 5070, co-developed with MediaTek and joined by Nvidia's proprietary coherent chip-to-chip interconnect (NVLink-C2C).

The Lenovo Yoga Pro 9n is the performance-centric model, offering 2 NVMe SSD slots and a total advertised storage capacity of 4 TB, while the non-Pro model caps at 2 TB. It also offers an extremely color-accurate 15.3-inch 2.5K PureSight Pro OLED that runs from 48 to 165Hz at 1100 nits peak brightness, plus a large 92.5 Whr battery with rapid charging that lets it eke out an advertised 3 hours of battery life after 15 minutes of charging. It also offers 2 USB-A and 2 USB-C (USB4) ports; the latter support DisplayPort 2.1 and USB PD 3.0 for power users, and it also includes an HDMI 2.1 connection and an SD port.

With WiFi 7 and BT 5.4 under the hood, plus a 9.2MP IR camera and a quad-speaker setup, the Pro 9n is built for creators who need plenty of connectivity in a slim, portable chassis.

For those who need a slightly larger screen and potentially a 2-in-device, the Yoga 9n skips the 'Pro' moniker but offers a 2.8K OLED display with a slightly lower capped refresh rate (30 to 120Hz), half the maximum memory configuration, and a slightly larger battery (99.9 WHr), even as it sees its weight increase to 1.94KG as a result.

A portable for-local AI offering that holds its own

For business buyers looking to localize their AI needs, run large proprietary AI models, or keep data on-device, the unified memory pool both Lenovo offerings bring to the table is essentially their biggest selling point.

This is in sharp relief from how the first wave of Copilot+ PCs stressed AI performance as a unit of NPU TOPS, even as the emergent bottleneck was that of memory capacity and bandwidth, where both laptops excel.

A machine that holds a large model in memory can essentially run inference on material that never leaves the device, even as both laptops offer a decent mid-range GPU that can generate more tokens than most comparable laptops for similar models.

This is crucial for firms that cannot send client documents, patient records, case files, source code, or export-controlled technical data to a third-party cloud API; this is not just a performance feature but a compliance one, and it marks the difference between using a model on real work with information that is often sensitive versus on test data.

The laptops also bring relief for developers who spent the last few years trying to use unified memory-based Apple laptops to work with Nvidia's CUDA stack with varying amounts of success, to build locally on a computer that essentially eliminates that compatibility and testing gap by allowing it to run the CUDA stack natively on the RTX Spark-based machines.

One could argue that many applications still have compatibility issues on ARM-based CPUs, but that gap is narrowing as Microsoft continues to publish updates and emulation improves, and as more developers publish ARM-centric compilations of their software.

Despite their AI-centric focus and catering to high-end professional users, Yoga generally isn't where Lenovo's business customers are found; its business fleets run on ThinkPad, with ThinkShield security tooling, business-grade manageability, extended parts availability, and the lifecycle commitments that enable predictable refresh cycles.

Lenovo has not announced pricing for the Yoga Pro 9n or the Yoga 9n currently, stating that it will do so at launch, even as the accompanying Snapdragon 8 Elite-powered Lenovo Yoga Tab Plus Gen 2 and MediaTek Dimensity 9500s-powered Lenovo Yoga Tab Gen 2 both reach shelves this September with price tags of $999.99 and $729.99, respectively.

• Lenovo announced the ThinkBook 14x Gen 2 at IFA 2026: a 990g notebook with up to a 14-inch 2.8K 120Hz OLED option, Intel Core 7 Series 3 silicon, and a starting price of $999.99 in Q1 2027
• It is the only computing product in an AI-branded launch with no TOPS figure and no Copilot+ claims as part of its published spec sheet
• The laptop does make compromises, skipping Thunderbolt and USB4 connectivity, WiFi 7 at half the channel width of the Arm-based ThinkBook 14 Gen 9 it launches alongside, and an HDMI 2.1 port that caps out at a 4K 60Hz output

Lenovo announced the ThinkBook 14x Gen 2 at Innovation World during IFA 2026: a 990g notebook running Intel Core 7 processors from the Series 3 generation, starting at $999.99 and available for purchase in Q1 2027.

It arrives as part of a series of launches focused on what Lenovo calls "Hybrid AI for Business," but it's the only computing product in the press release that makes no AI claims out of the box.

It offers excellent general-purpose compute capabilities but cuts back in some key connectivity areas that might deter power users.

A performant, lightweight option that cuts back on some key features

The higher-end version of the Lenovo ThinkBook 14x Gen 2 offers a 14-inch 16:10 2.8K OLED running at 120Hz with 100 percent DCI-P3 coverage, 500 nits, and a bent anti-glare finish, which is an excellent offering in a market teeming with cheaper options. For those unwilling to pay the premium it will inevitably command, the ThinkBook 14x also offers a WUXGA LCD alternative with the same 120Hz refresh rate, 100 percent sRGB, 400 nits, and optional touch.

Lenovo's press release says the ThinkBook 14x Gen 2 "delivers premium mobility in an ultra-thin, lightweight design built for everyday productivity," and it is hard to argue otherwise for a laptop that holds its own in a market that is getting pricier thanks to soaring component costs.

It does, however, make significant cuts to get there; the most prominent is the lack of Thunderbolt or USB4 ports, despite sporting a CPU (Intel Core Ultra 7 Series 3) that supports them. It also cuts Wi-Fi support to 160MHz versus 320MHz on the accompanying ThinkBook 14 Gen 9, effectively halving its maximum data throughput.

Despite this drawback, it has two USB-C ports that currently offer USB 3.2 Gen 2 connectivity at 10Gbps, which should suffice for most mainstream users even if the four-Thunderbolt-lane standard of Intel's Core Ultra Series 3 platform controller remains unused.

It also comes with an 18Gbps HDMI 2.1 port (TMDS) that caps maximum output at 4K 60Hz, which is arguably a lesser concern for a laptop that lacks Thunderbolt support, which already limits its potential to be paired with an eGPU and is unlikely to offer much to gamers, who would otherwise be the primary audience for a high refresh rate at a 4K resolution.

Lenovo has not published the AI TOPS capabilities of the as-yet-unnamed Core Ultra 7 Series 3 CPU it is pairing with the ThinkBook 14x Gen 2, even as the ThinkBook 14 Gen 9, announced alongside it features a Snapdragon X2 Plus with an explicitly stated 80 TOPS AI performance by Qualcomm and Copilot+ support out of the box.

One could argue that the AI aspect being skipped is intentional, and the ThinkBook 14x Gen 2 caters to a vastly different crowd, something that is easy to reconcile with, but the compromises in connectivity hit hard for any power user looking for a capable but feature-packed 14-inch laptop in the segment even if Lenovo has indirectly made it abundantly clear about what its target audience is: casual users that need a thin, but performant 14-inch laptop.

• Lenovo announced the ThinkCentre X Ultra at IFA 2026, a 1.6-liter desktop with its max configuration offering up to AMD's top-of-the-line Ryzen AI Max+ PRO 495 APUs
• It launches in November 2026, starts at $3,699, and comes with up to 128GB of unified memory under the hood
• Users can configure four of these together to leverage as much as 512GB of unified memory for local needs

Lenovo announced the ThinkCentre X Ultra at its Innovation World event during IFA 2026: a 1.6-liter desktop built around AMD's Ryzen AI Max+ PRO 495 with up to 128GB of unified memory, starting at $3,699, shipping in November 2026.

The company calls this offering a new class of desktop for agentic AI, and it can be configured to cluster up to four systems, effectively pooling processing power and memory to run large AI models locally.

The added compute and memory capacity lets users run longer context windows and multi-agent workflows without turning to cloud-hosted alternatives, while keeping data localized.

Plenty of scalable power under the hood

The Ryzen AI Max+ PRO 495 is the flagship of AMD's Gorgon Halo refresh, pairing 16 Zen 5 cores with a 40-compute-unit Radeon 8065S integrated GPU and an NPU rated at roughly 55 TOPS. Its defining trait is the shared memory pool: the CPU and GPU address the same LPDDR5X memory under the hood, so it can effectively hold and run models that a discrete, consumer-grade GPU with 24GB or 32GB of VRAM cannot.

Lenovo pairs it with its enterprise-class ThinkShield security, AMD's PRO technologies, and DASH out-of-band manageability, plus the self-healing BIOS that runs across the ThinkCentre line, and integrates the AMD Ryzen AI Developer Center for preconfigured tools, models, and workflows across both Windows and Linux.

The Yoga laptops unveiled alongside it also reach 128GB of unified memory, but they don't offer the ability to cluster together for more memory or the additional hardware you may not need for a localized AI server. The price might be an issue for many looking to hook up four of these devices together; however, assuming a device cost of $3700 for a 128GB model, one would need nearly $15,000 before factoring in connectivity costs to build a 512GB memory cluster based on the ThinkCentre X Ultra.

Lenovo has not, however, said how connectivity will work, what bandwidth units will have when running four in tandem, or what the performance implications will be for such a configuration, even as its listed specs include dual Thunderbolt 4 ports rated at 40Gb/s each. The larger memory pool also might not translate to performance; while AMD's 16-core Zen 5-based configuration is fast as processors go, the integrated GPU is considerably slower, even when running together, versus something like an Nvidia H100 that can be rented for a few dollars an hour online.

For those looking for something visually attractive that doubles as a monitor for what the system is up to, the ThinkCentre X Ultra also has adaptive lighting under the hood that provides real-time visual feedback. However, whether it stacks up two months later, as an increasing number of Ryzen AI PRO 400 APUs make it to developers and AI users across the world, joining an ever-increasingly competitive fray, remains to be seen, even if you can rig four of them together, in addition to Lenovo's enterprise offerings being integrated in tow.

• FBI warns of rising OAuth consent phishing attacks exploiting legitimate app permissions
• Victims tricked into granting malicious apps access, enabling email reading and sending
• Password changes don’t help; users must revoke tokens in app security settings

Hackers found a way to access your data, read your messages, and even send emails to your contacts, without ever needing your password or other login credentials. All they need from you is a single click on a completely legitimate, well-known platform.

The technique is called “OAuth consent phishing”. It’s been around for more than a year and it’s gotten popular to a point where even the FBI is taking note. Earlier this week, the law enforcement agency issued a new public service announcement, via its Internet Crime Complaint Center (IC3), warning Americans about the threat.

OAuth (Open Authorization) is an internet standard that allows users to give apps access to their account on another service, without giving the app their password for that service. For example, when users install a new app, they have the “Continue with Google” option. When they click it, they are asked if they allow the app to access their email. If they approve, Google gives that app a special access token, which allows the app to access the user’s Google account without ever seeing the password.

Pulling off an OAuth attack

So, to pull off an OAuth attack, the threat actor must first trick Google (or Microsoft, or any other company providing the service) and get their (malicious) app registered on the platform. Then they would reach out to their target via instant messaging, while impersonating government officials, media, and other publicly known personalities, and sharing a link to what appears to be a document.

The link redirects the victim to a legitimate service (for example, Google), where they are asked to grant permissions to the malicious app. If they approve, the attackers gain access to their email accounts with which they can do almost anything.

To make matters worse, simply changing the password does not fix the issue. The only way to eliminate the threat is to revoke the access token that was given, which can be done in the application security settings.

The FBI did not say who the threat actors were or who they were targeting, other than they were “prominent victims”. Their family members were being targeted, as well.

Via The Record

• Thomson Reuters confirmed March 2026 breach of its C‑Track court management system
• Incident affected courts in 11 US states, Ontario, and the US Virgin Islands
• No operational disruption; scope of exposed records still under investigation, no misuse reported yet

Thomson Reuters, the IT company behind the Reuters news agency, suffered a cyberattack a few months ago, exposing certain court documents to the attackers. In a brief announcement published earlier this week, it seems Thomson Reuters only noticed the intrusion now, months after it was already over.

Here is what happened: Thomson Reuters operates a court case-management system called C-Track. It is a tool used by different courts to manage things like cases, filings, hearings, and schedules. It is used by courts in several US states, the US Virgin Islands, as well as Ontario, Canada.

On June 30, 2026, Thomson Reuters detected unauthorized activity in one of its cloud environments, prompting an investigation which later determined that an unauthorized threat actor broke in and obtained some C-Track files. This happened in March 2026.

Investigation underway

So far, the incident is confirmed to have taken place across 11 US states (Alabama, Pennsylvania, Kentucky, Montana, Nevada, North Dakota, South Carolina, Tennessee, Ohio, New Hampshire, Wyoming), the U.S. Virgin Islands, and Ontario, Canada, exposing court records and personal information. Ontario's three Chief Justices confirmed it, as well, saying Thomson Reuters notified Ontario's Ministry of the Attorney General on July 23.

A more detailed investigation is currently underway, and all relevant authorities have been notified, it was said. At press time, Thomson Reuters did not yet determine exactly what information was accessed, or how many people were affected. The good news, however, is that there is currently no evidence of identity theft resulting from the incident, and there is no indication that systems handling court-related financial transactions were affected.

C-Track itself remains operational, as well. No threat actors have yet claimed responsibility for the attack or threatened to leak the files to the dark web.

"There has been no operational disruption to C-Track as a result of this incident," a Thomson Reuters spokesperson said. "Our products and services remain fully operational and are safe ​to continue to use. Independent ​cybersecurity experts assisted in ⁠the investigation and validated the remediation measures implemented."

I've been looking through Labor Day laptop deals, and for the specs on offer, this is my favorite one for business professionals so far, with the Dell 15.6" 2K Touchscreen laptop now $650 (was $1100) at Best Buy.

With that massive $450 discount, you're getting a 13th-generation Intel Core i7-1355U processor, 16GB of DDR5 RAM, and a 512GB PCIe SSD, which is good enough for everyday work, multitasking, browsing, and streaming.

The 15.6-inch 2K touchscreen adds even more value. And although there are some compromises, including integrated graphics, I haven't seen many Labor Day laptop deals that give you this much for under $650. For more laptop deals and WFH essentials, see our round-up of the best Labor Day home office deals.

Why we recommend it

At $649.99, you're getting a lot of laptop for your money. The 13th-generation Intel Core i7-1355U has 10 cores, 12 threads, and a maximum boost speed of 5GHz, giving it plenty of power for everyday tasks.

16GB of DDR5 is a solid plus at this price, and the 512GB PCIe SSD provides a decent amount of fast storage. You also get a 15.6-inch touchscreen, Wi-Fi 6, USB-C, two USB-A ports, HDMI, an SD card reader, and a full numeric keypad.

For more top performers, see our guide to the best business laptops we've tested.

Price context & historical value

Best Buy normally lists this Dell laptop at $1,099.99, but its Labor Day deal brings the price down to $649.99, putting it firmly into mid-range laptop territory.

Of the Labor Day laptop deals I've seen so far, this is one of the best for anyone who wants plenty of everyday performance without spending anywhere near to $1,000. It isn't the cheapest it's ever been though. It was priced at $599.99 at Best Buy in August this year.

Should you buy it?

✅ Buy the Dell 15.6" laptop if...

If you want a powerful everyday Windows 11 laptop for most tasks, $649.99 is an excellent price. The Core i7 processor and 16GB of DDR5 RAM gives it considerably more staying power than a cheaper laptop with 8GB of memory.

❌ Skip the Dell 15.6" laptop if...

If you want a laptop for gaming, creative work, or anything else that depends heavily on graphics performance, I'd look elsewhere. The integrated Intel UHD Graphics are the biggest limitation here, and there's no dedicated GPU.

The Catch: What to know before you buy

The display is one area where Dell has clearly kept costs down. It's rated at only 220 nits of brightness with 45% NTSC color coverage, so it's better suited to indoor everyday use than working outside or doing color-sensitive work.

There are a few other omissions to be aware of, including the lack of a backlit keyboard and Ethernet port, plus the webcam is limited to 720p.

• Shop all laptops at Best Buy

Western Digital's WD Red Pro NAS drive line is designed for businesses small and large looking to max out their storage. Having benchmarked several, it remains one of our favorite internal drive brands - and right now, the WD Red Pro 16TB NAS drive is now $690 (was $705) at Amazon, so long as you tick the coupon box.

Designed for demanding environments, Western Digital rates this model for workloads of up to 550TB per year and continuous 24/7 operation. I've also spotted the NAS drive for the same price here at Newegg when you use code LDSF324.

• The WD Red Pro 16TB is also $690 (was $705) at Newegg with code LDSF324

Why we recommend it

The WD Red Pro is specifically designed for demanding NAS environments, with a 7,200 RPM spindle speed, 512MB cache and CMR recording. It's rated for continuous 24/7 operation, with workloads up to 550TB per year.

It can be used in RAID-optimized NAS systems regardless of the number of drive bays, and NASware technology is designed to improve performance and compatibility. There's also a five-year limited warranty.

In his 4-star review of the smaller 14TB model, our expert Mark said it was "difficult to argue with the resilience of this drive," adding that "lots of resilience tricks and low power consumption are the hallmarks of this design."

Similarly, the 24TB model received 4 stars in his review, where he praised Western Digital's Red Pro line as offering "good performance and massive capacity. And, if the business can afford them, these are a good choice."

For more options, take a look at our roundups of the best NAS hard drives, and the best 167 hard disk drives worth buying.

Also consider

Price context & historical value

At $689.99 after the Amazon coupon, you're saving $15 against the current $704.99 price. That's only a little over 2%, so this is only really worth snapping up if you desperately need to upgrade early.

The WD Red Pro 16TB has been considerably cheaper over the past year, dropping to around $270 in late 2025 before prices began climbing sharply in 2026.

You can also get the drive for the same $689.99 price at Newegg. It's currently $704.99 but you get $15 off when you apply promo code LDSF324.

Should you buy it?

✅ Buy the 16TB WD Red Pro HDD if...

You have a heavily used NAS and want to add a substantial amount of storage without occupying several additional bays. Its high workload rating also makes more sense for an always-on NAS than using a standard desktop hard drive.

❌ Skip the 16TB WD Red Pro HDD if...

Your storage requirements are relatively small. or you have several empty drive bays available. Smaller-capacity NAS drives could give you the space you actually need for less.

The Catch: What to know before you buy

The obvious problem is the size of the discount. Saving $15 on a $704.99 hard drive isn't massive and this model has been considerably cheaper before. Unless you need another 16TB of NAS storage now, there's a strong argument for waiting to see if a better discount arrives shortly.

• Shop all internal hard drives at Amazon

• Not a single agent scored the full 20 out of 20
• Claude for Chrome performed better than the ChatGPT Chrome Extension
• With performance varying by testing category, Decodo advises selecting an agent based on planned usage

New Decodo research has criticized AI agents for still not being able to conduct real-world browsing tasks autonomously, including tasks like form filling, completing transactions, having cross-tab awareness and handling third-party integrations.

In fact, the study analyzed 45 AI agents across 10 different capabilities and found that not a single one could achieve the maximum score of 20.

The testing is also said to have exposed discrepancies between what vendors and AI developers say their agents are capable of, and what they can actually deliver on.

Agentic AI isn't at the level of autonomous browsing, yet

Claude for Chrome was the highest-scoring agent, reaching 18 points – two below the theoretical maximum. Its OpenAI counterpart, the ChatGPT Chrome Extension, fell short with a 14-point score.

Decodo argues that agents most commonly fall behind on transactions – the lowest-scoring category with an average of 0.43 out of 2. The study found that, while they can often reach the checkout stage, they can't actually complete a purchase on behalf of the user.

Even if an agent is technically capable of making a purchase, the paper warns that it still might not have the best safeguards in place to keep sensitive information like credit card numbers safe.

Safeguards is a major theme in Decodo's work, with the research also calling out multi-step workflows for lacking sufficient safeguards. More than half of the agents capable of multi-step workflows lacked any documented safeguards before conducting irreversible actions.

While current agentic technology still doesn't deliver on its promises, one type may emerge as the winner. Decodo found several browser-native agents to score full marks for cross-tab awareness.

"Match the tool to the job, not to the longest feature list," Product Marketing Team Lead Gabriele Vitke explained, urging AI agent users to consider their own needs instead of buying into marketing.

• 22% expect their policy to offer full coverage, 10% expect it to fall short
• Data breaches and reputational damage are major concerns
• Companies should look at finances before considering operational recovery readiness

New research from Cohesity has revealed that many UK businesses could be significantly overestimating the protection they get from cyber insurance policies, with just one in five (22%) British CEOs believing their policy would cover both the additional costs and lost revenue that an attack could lead to.

A third expect it would cover the additional costs only, another third believe their policy is only sufficient for lost revenue, and a further one in 10 did not expect it to cover either of the two categories.

The report's conclusion is that cyber insurance in its current state for many UK businesses is only enough to transfer some of the financial risk – but not enough to restore systems, data or operations.

Cyber insurance policies don't provide enough cover

According to the study of 100 CEOs from large enterprises, businesses expect a cyberattack to reduce their revenue by an average of around 15%, but many businesses lack a detailed understanding of how much an attack could actually end up costing them. As many as one in five (21%) haven't even conducted business impact modelling.

Among CEOs' biggest fears are data breaches (49%), brand and reputational damage (38%), high recovery costs (36%), revenue loss (34%) and production downtime (30%). They're all either financial concerns or incidents that could lead to financial loss, and yet it's clear that policies are unlikely to offer enough cover.

With many totally unaware of the potential impacts and the extent of their policy's cover, Cohesity urges businesses to start off with calculating financial exposure and understanding what their policy covers.

After that, they can go on to prove that critical systems can actually be recovered, because without an insurance payout, this would likely not be possible.

"Organisations must be able to identify the systems and data needed to keep the business operating, assigning clear responsibility for recovery decisions and regularly testing whether critical services can be restored securely," UK&I VP Fraser Hutchison explained.

The Munbyn RW403B remains one of the best shipping label printers we've ever tested, and it's the one our senior printer editor regularly recommends if you're running an ecommerce store or a small business. And currently, Munbyn's Bluetooth thermal label printer is down to $80 (was $120) at Amazon.

During our own testing, we found it easy to use, impressively quick to print, and actually fun to use. It delivered excellent results across a range of labels, postage notes, barcodes, and stickers with support for sizes from 1.57 to 4.25 inches wide.

The RW403B offered us a dedicated way to print 4 x 6-inch shipping labels without having to buy ink or toner. It connects over Bluetooth and works with Android and iPhone devices, as well as Windows PCs, Macs and Chromebooks. In the UK, the Munbyn RW403B is now £70 (was £95) at Amazon.

Why we recommend it

Munbyn says its DAC technology automatically calibrates the printer to reduce label misalignment, while the 0.1mm font legibility should keep small text and barcodes clear. It's also rated at 60dB, which makes it better suited to a home office or shared workspace where a noisy printer could quickly become irritating.

In his 4.5-star review, our senior printer editor Jim said: "it’s easy to set up and operate," and "the robust design feels like it’s built to last and the print quality is better than most label printers."

He went on to explain, "After your initial outlay, there’s no ink cost to think about and thermal labels can be bought inexpensively."

Scroll the gallery below for more images taken during our testing.

Price context & historical value

At $79.99, you're saving $40 against the usual $119.99 price, which works out to a solid 33% discount. It has been cheaper in the past, but not hugely. We've seen it as low as $76, which is just $4 less than the current price.

Should you buy it?

✅ Buy the Munbyn Thermal Label Printer if...

You're regularly packing and shipping orders and want to streamline the process. Bluetooth connectivity means you can print from any device. It's absolutely ideal for small business and ecommerce use.

❌ Skip the Munbyn Thermal Label Printer if...

You need colorful labels, graphics or branding. This is a monochrome thermal printer designed primarily for practical labels, so you'll need a different printing technology if presentation and full-color output are required.

The Catch: What to know before you buy

This is a specialized printer and while its maximum 4.25-inch print width is ideal for shipping labels and similar jobs, but it can't handle regular letter-size documents.

It's also worth considering how often you'll actually print labels. The convenience is easy to justify for a small business or frequent online seller, but occasional users may be perfectly happy continuing to output shipping labels on an ordinary printer.

• Shop all label printers at Amazon

AI tools can automate large-scale tasks at a fraction of the usual cost, which makes them a great option for solo or small business setups.

If you can't invest in a sizeable employee headcount just yet, you can now limit your hires to key roles or just have a few contractors while everything else runs automatically. It's not a replacement for an actual large-scale enterprise operation, but it's a good enough solution to get your feet in and expand more thoughtfully.

So, here are 7 accessible AI platforms that I'd personally use if I were launching a new business in 2026.

Do you need AI to run a business in 2026?

No, not strictly. People built profitable small businesses before AI came along, and obviously, plenty still do. What's changed is the cost of not using AI relative to competitors who can automate the bulk of their work to move faster and scale up.

AI works best as a way to reclaim time on repetitive tasks, not as a replacement for anything that requires judgment. A chatbot can draft your customer email, a task manager can organize your daily workflows, a text generator can come up with marketing drafts. It won't replace your judgment in client relationships, but it will take some load off your back.

Businesses that get the most value pick two or three tools that solve a specific problem. Rather than bolting on every AI tool you can find, start with whatever's eating the most hours in your week, and build out from there. Here are my personal picks.

7 useful AI tools for solopreneurs and small businesses

I've picked one standout per category so you're not choosing between five near-identical products. There's plenty of competition in each space, but the ones recommended here are specific to smaller operations and priced accordingly.

Writing: Jasper

Jasper remains one of the most capable AI writing platforms for small teams that need consistent output across blog posts, ad copy, and social content. It works from your brand voice and past content, so drafts sound less generic than what you'd get from a bare chatbot prompt.

Jasper's Creator plan starts at $59 a seat per month when billed annually, or $69 monthly, with a Business tier that adds more seats and workflow features.

It's not the cheapest writing tool on the market, but the output usually needs less editing than lower-cost alternatives, which matters when you don't have a copywriter on staff. If you're only writing the occasional caption or product description, a general chatbot might cover it, but Jasper earns its keep once content becomes a weekly commitment.

Customer support: Tidio

Tidio is built with small teams in mind rather than enterprise support desks, pairing live chat with an AI agent called Lyro that reads your website and builds its own knowledge base automatically. That means you're not stuck writing scripts or training a bot from scratch before it can answer real customer questions.

Tidio's free plan covers 50 handled conversations a month, which is enough to test whether it fits your support volume before paying anything. Paid plans start at $59 a month for higher conversation limits, and Lyro AI costs another $39/month for 50 automated conversations. Setup is straightforward enough that most owners can have it live on their site within an hour.

Bookkeeping: QuickBooks Solopreneur

QuickBooks built a stripped-down tier specifically for people running side gigs or one-person operations who need to separate business and personal spending without a full accounting course. Intuit's AI features categorize transactions, flag anomalies, and estimate quarterly taxes as you go.

Pricing ranges from free to $20 a month for the Lite tier, which adds unlimited invoicing and automated sales tax tracking. It won't replace an accountant once your finances get complicated, but it's a sensible starting point for keeping records clean from day one.

Just don't skip a real bookkeeper once revenue climbs past a side-gig level. AI categorization still makes mistakes that a professional would catch.

Task management: Motion

Motion combines your calendar, task list, and meeting bookings into one AI-managed system that automatically reshuffles your day when priorities shift or meetings run long. It's built for people juggling client work and admin without an assistant to protect their time.

The AI Workplace plan starts at $29 a month. That said, users are split on how intuitive the interface feels at first, so it's worth running the free trial before committing to annual billing. It's most useful if your calendar gets disrupted often, since the automatic rescheduling does the negotiating you'd otherwise do by hand.

Design: Canva

Canva's Magic Studio bundles AI image generation, background removal, and one-click resizing into the same editor most small business owners already know from making social posts and flyers. You can generate a product photo, clean it up, and reformat it for five different platforms without leaving the tab.

Canva Pro costs $18 a month or $180 a year and unlocks the full range of Magic tools, on top of the platform's existing template library.

For businesses without a design budget, it's usually the fastest way to look professional without hiring anyone. It's worth pairing with a proper brand kit setup early, so every asset stays consistent as more people touch your Canva account.

Email marketing: Mailchimp

Mailchimp pairs its email and automation tools with AI content generation that drafts subject lines, full campaigns, and basic segmentation based on your past sends.

The Standard plan, which unlocks the generative AI tools, starts at $11.95 a month for up to 6,000 monthly email sends. The free tier still exists but was cut back sharply in January 2026, so budget for a paid plan if email is core to how you reach customers.

It's a reasonable fit if you're already sending newsletters or promotional emails and want to speed up the drafting stage. But remember to treat the AI drafts as a starting point rather than the finished send, since generic subject lines still underperform ones written with your actual audience in mind.

Workflow automation: Zapier

Zapier connects the other tools in your stack so information moves between them without you copying and pasting. Its newer AI Agents feature goes a step further, letting you describe a workflow in plain language and have it monitor for triggers and act automatically.

The Professional plan starts at $19.99 a month when billed annually, unlocking multi-step workflows and AI-assisted automations. If you've ever manually moved a new customer's details from a form into your CRM and email list, this is the category that fixes it. The free tier is usable for simple two-step automations, so it's a reasonable place to test whether automation actually saves you time before paying for it.

Things you should be aware of

Every tool above collects your data to function, and it's worth reading what happens to it before you upload customer details or draft sensitive documents. Some vendors also train future models on your inputs unless you actively opt out in account settings, which isn't always apparent right away. Check the privacy or data policy page for each tool rather than assuming the default options are safe.

Another thing to keep in mind is that costs can also creep up faster than expected. Several established AI platforms bill per resolution, per credit, or per task rather than charging a flat monthly fee. Usage-based pricing looks cheap right up until it doesn't, so set a spending alert where the platform allows it. Also review your invoice against your actual usage, at least for the first couple of months.

The final problem is accuracy and liability. AI-generated content, whether it's a customer support answer, a bookkeeping category, or an email to a client, can be confidently wrong, and you're the one who has to answer for it if it is. Treat it as a first draft that needs a human check before it reaches a customer, a regulator, or your tax return, especially anywhere money, legal terms, or compliance are involved.

There is more technical content available today than any human being could read in a thousand lifetimes. Every topic has a dozen YouTube videos, three Substack posts, a GitHub repo, and a Reddit thread, most created in the last six months and, in many cases, technically accurate.

And yet most of the professionals I talk to say they don't know what to trust. They can't tell what’s important to read first, or which of 10 plausible answers is the one that holds up. That was true before AI, and AI has made it more true.

For most of the history of technical publishing, editing and verification were the same process, and that process was slow and expensive. Getting a book out took years. We found an author, vetted them, had them work with an editor, and checked their claims with technical reviewers.

A lot of that time went into separating what was correct and useful from what was confusing or only sounded right. It was laborious, but it meant a reader could depend on the claims on the page.

The credibility of the book, and of the publisher behind it, mattered as much as the information itself. When the cost of production drops to zero, that credibility becomes worth more, not less. Content is easier to make than ever, but without a transparent process behind it, readers have no idea where the knowledge came from or whether it holds up.

As Jasmine Sun puts it in “The Independent Writer’s Advantage in the Age of AI,” "Trust is not about information and its quality alone. It's about the messenger. It's about who says it and their track record and what they've told me before." A practitioner has confidence in a source because someone she respects has put their reputation on the line for it.

They believe what the author is saying because the publisher has a history of being right and of correcting itself when it isn't, and because the work is attributed and verifiable.

Expertise is alive, and it compounds

The corpus matters, but it's the assurances around it that are hard to replicate, and that comes not just from the people who produce the content but from the people whose judgment vouches for it. Sometimes a creator brings their own credibility with them. Other times, the publisher spots someone unknown and lends them its own.

The art critic Dave Hickey said this about gallery owners in Air Guitar: They gain status from the famous artists they represent and share it with emerging talent who have something to offer but who haven't had the chance to earn a reputation.

Expertise is alive, and it compounds Expertise is a living thing, continuously expanding. Content starts to decay the moment it’s published, because frameworks evolve, libraries deprecate, and yesterday's best practice becomes today's security incident. Keeping expertise alive requires a pipeline of people who stay current and an editorial layer that notices when something has gone stale, and either retires it or calls for a fix.

That pipeline isn't something you switch on when an author has a book to ship. Content sits at the center of our platform, but we think about it in pace layers. Some advice is timeless, some moves but has a long shelf life (some of our books are still in print after nearly 50 years!), and some changes weekly.

We work with experts at each pace layer, capturing what lasts while doing our best to keep pace with an industry that seems to have changed every time we wake up.

We have relationships with hundreds of the best practitioners in the world, and our job is to keep them engaged continuously, with quick takes when something breaks, structured responses when major research drops, and live sessions on emerging topics while they're still emerging.

Trust is earnt

An institution doesn't stamp trust onto content. In a technical community, trust is conferred in both directions. A practitioner earns standing because people who already have standing engage with her work, cite it, argue with it, and build on it. That insight was the whole idea behind PageRank, Google's first great innovation. A page mattered because other pages that mattered linked to it. Reputation works the same way.

The audience isn't just consuming reputation signals; it's generating them. When a senior engineer whose judgment others respect says out loud that something is worth reading, she spends a little of her own credibility; the author gains a little; and everyone watching recalibrates whom to trust next time.

When we put our mark on someone's work, we aren't the sole source of its credibility. We're amplifying a judgment the community is already making and adding our own track record to it. The reader who finds it reliable hands status back to the source.

When the readers are machines

Human practitioners aren't the only ones who need trusted engineering knowledge. The AI systems now sitting in every workflow, the coding and debugging agents and architecture advisors, need it just as badly since most of them are built on scraped web data and documentation that was stale before it was ever indexed. They're fluent, but they're wrong often enough that you can't just take their word for it.

The stakes grow with AI tools increasingly being used to generate not just provably correct types of content like code, which either works or it doesn’t, but persuasive documents in fuzzier areas like hiring, strategy, and so on. Like everyone else leaning on these tools, we are reckoning with the consequences of the ability to talk to a model and get back something that looks smart at a glance.

A few rounds in, the slop is still there. In the last few months, maybe 10 times as many documents have crossed our desks, from new product ideas to strategic plans and proposals. But the ease of generating the text hides the fact that either the model or the person prompting it doesn't actually know what they’re talking about. Knowledge workers need ways to ground their work in insights from human experts, particularly when that work is AI-assisted.

So we’re building tools that let agents draw on our repository of expertise to support their proposed decisions.

Credible sources are particularly important when thinking through and justifying important choices. Our CTO, Andrew Odewahn, describes the shift this way: "18 months ago, it was all about how to get engineers to be more productive, but now it's about how to get organizations to make better decisions. The engineering tasks are moving away from coding output to planning."

For planning tasks like comparing implementation approaches, you need expert-over-your-shoulder guidance for contextual decision-making. You can’t just rely on an LLM's best guess to solve your problem. Trust is foundational because the expertise behind it stays genuine, practical, and human.

We've featured the best AI website builder.

This article was produced as part of TechRadar Pro Perspectives, our channel to feature the best and brightest minds in the technology industry today.

The views expressed here are those of the author and are not necessarily those of TechRadarPro or Future plc. If you are interested in contributing find out more here: https://www.techradar.com/pro/perspectives-how-to-submit

No business owner likes the hassle of managing appointments. It could be a missed appointment or a rescheduled one where the client wasn't informed of a change. Poor scheduling doesn't just cause headaches, but it can cost valuable money.

If you'd like a streamlined scheduling workflow that takes the stress out of booking, rescheduling, canceling, and paying for your services, then you should take a look at Acuity Scheduling from Squarespace. With plans starting from $16 per month, it doesn't cost the earth either.

We gave it a solid four stars when we reviewed it, praising its integration into Squarespace, reporting that shows appointment trends and client behavior, and its excellent message alerting system.

Acuity Scheduling is a win for business owners and a win for your clients.

Manage your schedule like a pro

Acuity Scheduling features we love

Calendar management

Acuity Scheduling enables you to run your business on the go with a mobile app. Being able to manage your schedule wherever you are means all your appointments are easily taken care of. And with syncing support for personal and business calendars, you can easily minimize double-booking. Beyond this, you can get advanced reporting about appointments and no-shows.

Revenue boosters

Acuity Scheduling doesn't just make your life easier; it also enables you to maximize your revenue. This can be achieved by offering packages and recurring sessions as well as creating subscriptions for routine services. It's also possible to promote gift certificates and reward clients with discount codes.

Secure payments

Let Acuity Scheduling take care of payments with integrations for Stripe, Square, or PayPal. These services enable you to collect prepayment or a partial deposit or securely store credit card details at booking. You can also accept payments quickly via tap-to-pay, integrated card readers, or secure payment links. This takes all the stress out of managing your payments

• Baylor Genetics confirmed a June cyberattack affecting 2.8M patients and employees
• Stolen data includes medical test results, insurance info, and some SSNs/financial details
• Operations continued; no misuse seen yet, but no group has claimed responsibility

Baylor Genetics, a US-based clinical diagnostic laboratory, suffered a cyberattack in which it lost sensitive data on 2.8 million people - both patients and employees.

In a security update posted on its website earlier this week, the company said it spotted the intrusion in a “limited portion” of its IT environment on or around June 15. Subsequent investigation determined that both patients and employees have had their data stolen, including those who are not working at Baylor anymore.

For patients, crooks stole names, dates of birth, medical testing information, laboratory test results, and “potentially health insurance information, as well as Social Security number”. SSNs, Baylor Genetics stressed, were taken from a “very limited subset of patients”.

No attribution yet

Regardless, fraudsters who know the details about medical testing and lab results have more than enough information to launch highly sophisticated, personalized phishing attacks that can lead to ransomware infections, business email compromise, and more.

For certain current and former employees, the attackers nabbed Social Security numbers, government-issued identification numbers, and financial account information, ideal for wire fraud.

In the security update, the company did not discuss the identity of the attackers, or the number of affected individuals. However, in a separate report filed with the US Department of Health and Human Services, Baylor reported the number of victims as 2,810,878. It added that at the time of publication, there was no evidence of confirmed identity theft, fraud, or misuse of personal information stolen in the attack.

It also said the incident did not impact its everyday operations which continued as usual.

Usually, data theft incidents like this one are followed by public disclosure from the perpetrators, who name-and-shame their victims in an attempt to get them to pay a ransom demand. So far, no threat actors claimed responsibility for this incident.

Herman Miller is iconic in the world of ergonomic office furniture, and its range of pioneering desk chairs and desks have consistently impressed us during testing. And that includes the Jarvis Bamboo standing desk, currently down to the $994 (was $1325) in Herman Miller's big Fall sale.

This premium desk has some of the highest build quality of any we've reviewed, with all the features a professional requires from a sit-stand model. As befitting an executive-grade desk, this model, with its 25% discount, features a broad 48x27-inch desktop, black frame, a three-stage height range with programmable presets, and powered grommet. In the UK, a smaller Jarvis Bamboo is down to £645 (was £860) at Herman Miller.

• US: Save 25% in the Herman Miller Fall sale
• UK: See the full Herman Miller sale

Why we recommend it

The Jarvis has earned a strong reputation for its build quality and stability. Its powder-coated steel frame supports a bamboo desktop with a German-made, wear-resistant UV-cured topcoat. The motors can raise or lower it at up to 1.5 inches per second.

In his 4.5-star review, our expert Collin called it “a solid all-around offering with an impressive lifting capacity.” He went on to say: “This standing desk is excellent for those in small spaces or large open offices, who can customize it according to your needs.”

For more top-performing office furniture, see our guide to the best standing desks we've tested.

Also consider

Price context & historical value

At $993.75, you're saving $331.25 against the $1,325 original price, which works out to exactly 25% off. That's a substantial saving on a desk that rarely makes any attempt to compete with the hundreds of more affordable standing alternatives. That said, we have seen it cheaper elsewhere, with the price as low as $881 at other retailers.

Should you buy it?

✅ Buy the Jarvis Bamboo Standing Desk if...

You want a premium standing desk that can handle a substantial setup. Its 350-pound capacity gives you plenty of scope for multiple monitors and other hardware, while four programmable height presets make switching between preferred positions quick and easy.

❌ Skip the Jarvis Bamboo Standing Desk if...

You rarely change position once you've settled down to work. The Jarvis's electric adjustment is a major part of what you're paying for, so a high-quality fixed desk could make more sense if you know you'll spend virtually the entire day sitting.

The Catch: What to know before you buy

Even after the huge discount, this is still a nearly $1000 desk, and there are plenty of electric standing desks available for a fraction of that. You're essentially paying a premium for the materials, lifting capacity, finish and overall quality rather than simply gaining the ability to work standing up.

The warranty also varies by component. The desktop is covered for five years and the frame, motors, mechanical and electrical components for seven years, but the powered grommet and surge protector are only covered for one year.

• Shop all Herman Miller standing desks

In banking and utilities, regulators define certain systems as essential. An essential system is one whose failure would cause intolerable harm to customers, markets, or public safety. A payment platform in a clearing bank or a SCADA network in a power distributor, for example, carries the highest governance obligations: continuous monitoring, validated change control, and demonstrable resilience.

The policy environment – the accumulated rules across firewalls, cloud controls, and microsegmentation – determines which of those systems can reach each other, which connections are blocked, and which exceptions still apply. Collectively, these rules form the security policy control plane: the governance layer that translates business intent into access decisions across distributed enforcement points.

A misconfigured segmentation rule during a cloud migration can sever a payment service from its settlement platform; a temporary rule granting broad access from a development subnet into production can stay in place months after go-live because no one owns the removal.

Every firewall rule, segmentation policy, and access decision directly affects operational risk, and when the policy environment fails, the critical services it governs fail with it.

That makes the policy environment critical infrastructure in its own right.

Still governed like housekeeping

Despite this, many regulated organizations still manage their policy environments as operational tasks. Rules are added through change requests, and the accumulated result is rarely examined against what was intended. Ownership disperses as leaders change roles, and the reason why a specific rule came into being in the first place can only be found in a change ticket, if anywhere at all.

A CISO who would never accept a payment platform running without continuous monitoring or documented dependencies may accept both being absent from the policy environment that determines whether the platform is reachable. We can think of this as infrastructure-grade consequence with housekeeping-grade governance.

In banking, a policy failure that severs connectivity between settlement systems would constitute the disruption of an important business service. The FCA would take an interest in such a failure, since the loss of such a service could lead to intolerable harm.

In healthcare or energy, the consequences are different but the mechanism is the same: a misconfiguration that permits access from a corporate network into clinical systems in an NHS trust, or into operational technology in a power distributor, creates exposure at the level of essential service delivery. These are not hypothetical risks but the operational consequences of treating critical infrastructure governance as a simple housekeeping task.

Regulatory expectations point the same way

UK regulatory expectations increasingly support the same conclusion: the security policies governing access to important services must be managed with infrastructure-grade discipline. The FCA's operational resilience regime requires regulated firms to identify important business services and demonstrate, on an ongoing basis, that the supporting infrastructure remains within defined impact tolerances.

Ofgem assesses operators of essential services against the NCSC's Cyber Assessment Framework, asking whether defined security outcomes are being achieved on a sustained basis. The Cyber Security and Resilience Bill, expected to become law later this year, will extend similar obligations to data centers, managed service providers, and critical suppliers.

These frameworks are not prescriptive – none of them specifies which firewall rules an organization should have or how its segmentation policies should be configured. What they require is proof: that what the policy environment permits is what was intended, and that the organization can demonstrate this on an ongoing basis rather than reconstruct the evidence for each assessment.

Why the estate cannot meet that standard

Most policy environments were never built to meet that standard. In fact, most policy environments were never consciously or deliberately built at all. Instead, policy tends to accumulate as a by-product of delivery. Every project and migration adds rules, and almost none take any away.

Over time, the policy surface – the full body of rules and access decisions across enforcement layers – grows larger than the group of people who understand it, and the estate reaches a point where it can be operated but not explained.

Across regulated industries like banking, energy, and healthcare, that was sustainable under earlier regulatory regimes: periodic assessment, control-based audit, compliance frameworks that asked whether controls existed rather than whether they were effective. But this is no longer enough. The new standard requires continuous evidence that access is intentional.

The FCA's findings after a year of operational resilience self-assessments illustrate what this looks like in practice. Where regulated firms reported few or no outstanding vulnerabilities in the infrastructure supporting their important business services, the FCA often deemed the evidence too thin to determine whether there really were no vulnerabilities – or whether the vulnerabilities just hadn't been identified.

The lesson applies directly to security policy governance: an organization cannot credibly claim access-related vulnerabilities are controlled without evidence of what its policies permit, how they were tested, and whether weaknesses were remediated.

What infrastructure-grade governance requires

Too often, the response is to reach for more visibility and more documentation. But documentation will only ever capture a point in time; it cannot provide the continuous assurance regulators are coming to expect.

A CISO in a regulated firm needs more than a record of what the policy environment was configured to permit. Configuration and effective access are not the same thing. Security teams need to understand how rules, routes, objects, and enforcement layers interact to determine what can actually communicate.

Meeting the standard means reconciling the two: showing that what the environment permits in practice is still what it was intended to permit, and being able to show it without notice.

We separate where policy intent is defined from where it is enforced. Intent is held and maintained centrally, while enforcement remains distributed across firewalls, cloud controls, and microsegmentation in hybrid, multi-cloud, and multi-vendor environments.

Validation runs continuously against that intent rather than at review points: proposed changes are tested against policy before they reach production, and effective access is assessed on an ongoing basis for unnecessary exposure, inconsistency between enforcement layers, and divergence from business intent. What was permitted and what changed is retained as evidence.

The same CISO who would never accept a payment platform running without continuous monitoring, validated change control, and documented dependencies has to apply that standard to the policy environment that determines whether the platform is reachable.

The FCA, the NCSC's Cyber Assessment Framework, and the Cyber Security and Resilience Bill all point towards the same underlying question: can this organization demonstrate, continuously, that the infrastructure supporting its critical services is governed to the standard those services demand?

Answering it means knowing (and actually knowing – not assuming, not reconstructing at audit) what the policy environment permits at any given moment, and whether what it permits is what was intended.

We've featured the best antivirus software.

This article was produced as part of TechRadar Pro Perspectives, our channel to feature the best and brightest minds in the technology industry today.

The views expressed here are those of the author and are not necessarily those of TechRadarPro or Future plc. If you are interested in contributing find out more here: https://www.techradar.com/pro/perspectives-how-to-submit

• UK legislators propose “kill switch” laws to halt runaway AI, citing critical infrastructure risks
• Lord Clement‑Jones and MP Alex Sobel push amendments and new bills, backed by ControlAI advocacy group
• Similar efforts emerging in US

Sam Altman’s fear-based marketing for AI seems to have backfired, as now multiple legislators in the UK and elsewhere are calling for a “kill switch” law to be introduced.

According to the BBC, Liberal Democrats’ Lord Tim Clement-Jones proposed an amendment to the Cyber Security and Resilience Bill which would see the UK create a “vital safety net” to provide a “democratically accountable means to ‘halt a runaway system before it can compromise our critical national infrastructure’.” The capability would only be used as a last resort, Clement-Jones stressed.

The bill is currently being worked through in the UK Parliament, the BBC said.

Is there reason to worry?

But that’s not the only effort in the UK to put some reigns on AI. Apparently, Labour MP Alex Sobel plans to introduce an AI Security Bill later this month which, according to the BBC, would “effectively halt the development of superintelligent AI” and make the UK the first G7 country to do so.

The bill is supported by a campaign group called ControlAI, a UK-based nonprofit and advocacy organization focused on the risks posed by advanced AI. Its founder and CEO is Andrea Miotti, who previously worked at the AI safety company called Conjecture. Across the pond, US legislators are currently considering an AI Kill Switch Act as well, but the bill is still in very early stages of development.

Ever since the first ChatGPT model that was introduced in 2021, a debate has been raging whether or not AI will be net positive, or net negative, for humanity. While some argue that the discovery rivals the steam machine and that it will transform our lives beyond our wildest dreams, others are fearful of losing jobs, a collapsing economy, and a dystopian future devoid of humanity and emotion.

Marketing campaigns for ChatGPT and, in some measure, Claude, are not helping, either. Both companies have built models focused on cybersecurity which were advertised as “too dangerous” for the general public and instead were only given to a handful of organizations. Despite partial skepticism, many are worried that these models might severely disrupt the security of banking, critical infrastructure, and communications.

Via BBC

Let's say you've got an idea for a new business. A landing page is usually the first piece of "real estate" you invest in, long before you think of retail space or even a marketing brochure.

Websites cost a lot less today than they did ten years ago, but they cost even less if you know what you need (or don't).

In this guide, I'll show you how to set up a professional website for a solo or small business for as little as $13 in setup costs. You'll need a GitHub account, a free or low-cost vibe coding app, and $5 to $20 of spare cash for a domain registration.

But the best part is that you can scale this setup as you grow, adding just what you need without a single cent wasted. Slow season? You can also scale those resources back down. Here's exactly how I would structure it.

Launching a website in a day with $13: What to expect

My stack works best for landing pages, portfolios, small business sites, and simple lead generation forms. You'll end up with a mobile-friendly site on your own domain, built without any coding skills by describing what you want in plain English.

There's always a trade-off with these setups, which is scale. You can't collect payments, running complex workflows will crash your website, and storage is limited if you want to host audiovisual content.

But if you structure it right, you can keep space to expand things later without having to go through an expensive migration to a premium platform. There's no vendor lock-in, your existing stack is designed for scalability, and you're not stuck with any one provider.

Does it really cost $13?

Yes, because you'll only have to pay for the domain and a small subscription fee if you want to access one of the better vibe coding or AI website builders.

A .com domain from a mainstream registrar runs somewhere between $5 and $15 for the first year, which covers the budget in this guide with room to spare.

There's no upcharge for connecting your domain, AI tools don't always bill you for every additional token, and there are no additional monthly charges for hosting or storage, etc.

What tools will I need?

You'll need three things, and possibly a couple more if your site needs to store data or display dynamic content. Each category has many options with generous free plans. None of them require you to enter a credit card to get started.

Here's the exact stack you'll use to build and launch a website using this guide.

• A vibe coding tool. Look for one that supports code sync and export to an external repository, even on the free plan.
• A free GitHub account with a new repository that has GitHub Pages enabled.
• A custom top-level domain, such as a .com or .org, which costs roughly $10 to $20 a year.
• A free Supabase account for handling logins and storing form submissions. This one is entirely optional.
• A free AI code editor, like Cursor or Claude Code, installed on your computer for minor tweaks and updates. Also optional.

Step-by-step instructions for launching a $13 website in one day

All of these steps take anywhere from a few minutes to an hour individually. Work through them in order, and you should have a live site well before dinner.

Step 1: Describe your site to a vibe coding tool

Open your chosen vibe coding platform and describe the site you want in plain language. Mention the type of business, the pages you need (home, about, contact, pricing), and any specific sections like a lead capture form or testimonials block.

Most tools generate a working preview within a minute or two. From there, refine it with follow-up prompts:

• Ask for changes to layout, color scheme, or copy one section at a time, rather than everything at once.
• Request a working contact or sign-up form early, since this is often the trickiest part to get right.
• Check the mobile preview, since most visitors will land on your site from a phone.

Remember that on most free tiers, vibe coding tools will limit the number of prompts you can enter in a day. So make sure to read up on these limits and be certain about what you want so you can describe it verbatim. Also mention that you'll be hosting the website using GitHub Pages in your prompt itself, so that the AI can structure the code to be Pages-compatible.

Step 2: Connect a GitHub repository

Once you're happy with the design, look for the option to sync or export your project to GitHub. Most vibe coding tools have a one-click GitHub connection built in. You can also just export the code as a ZIP file and upload the contents directly to GitHub.

Create a free GitHub account, then create a new repository for the project. Keep it public so you can enable GitHub Pages, because Pages hosting is free for public repositories but requires a Premium plan for private ones.

Step 3: Turn on GitHub Pages

In your repository, go to Settings, then Pages. Choose the branch your site should deploy from (usually main) and save your changes.

GitHub will generate a free web address in the format yourusername.github.io/repository-name. This confirms your site is live, even before you attach a custom domain.

Step 4: Buy your domain

Pick a domain registrar and search for the domain name you want. Prices vary depending on the extension you pick, so a .com will usually cost more than a less common option like .dev or .site.

Stick to a mainstream registrar with clear pricing and no surprise renewal jumps. Skip any add-ons you don't need, like a premium DNS, to keep your total below $10.

Step 5: Point your domain at GitHub Pages

Back in your GitHub repository's Pages settings, enter your custom domain in the relevant field. This creates a small configuration file in your repository that tells GitHub which domain to serve your site from.

Then, in your domain registrar's dashboard, add the DNS records GitHub provides. This usually means a few A records pointing to GitHub's servers, plus a CNAME record if you're using a "www" version of your domain. These changes can take anywhere from a few minutes to a few hours to fully take effect.

Step 6: Set up Supabase (optional)

If your site needs to collect sign-ups, store bookings, or handle a login system, create a free Supabase project. Supabase gives you a hosted database along with authentication tools, without needing to manage a server yourself.

Most vibe coding tools have a direct Supabase integration, so you can usually connect your project with an API key rather than writing database code by hand. Ask your vibe coding tool to build the specific form or login flow you need. It will typically wire up the Supabase connection for you. When you connect or upload the files and code to GitHub, the integration will stay intact.

Step 7: Test everything before you call it done

Open your site on both desktop and mobile, and click through every link, button, and form. Submit a test entry through any lead capture form to confirm it actually reaches Supabase or your inbox.

Check that your custom domain loads correctly with https:// rather than throwing a security warning, since GitHub Pages issues free SSL certificates automatically once your DNS is set up correctly. Fix anything that looks off before sharing the link with anyone.

For small fixes, like a typo or a button that's misaligned, it's often faster to open the project in a free AI code editor like Cursor or Claude Code and make the change directly, rather than going back through your vibe coding tool's chat interface. Once you push the update to GitHub, your live site refreshes automatically.

What to do when you outgrow your $13 website

At some point, your free tiers will start to feel tight. Maybe you're approaching Supabase's storage or user limits, or your traffic has grown to the point where you want more control over performance and analytics.

The good news is that none of the upgrades below require you to rebuild your site from scratch. Because your code lives in a standard GitHub repository, you can move it to almost any hosting provider without losing your design or content.

• Upgrade your Supabase project to a paid tier once you're close to the free plan's storage, bandwidth, or user limits, rather than waiting until you hit a hard wall.
• Move hosting from GitHub Pages to a platform built for dynamic sites, such as Vercel or Netlify, if you need server-side features GitHub Pages doesn't support.
• Add a content delivery network in front of your site once traffic grows, so pages load quickly for visitors regardless of where they're located.
• Bring in a developer to review and harden any AI-generated code before it handles sensitive customer data, particularly around authentication and payments.
• Set up proper analytics and monitoring so you know when you're approaching a limit, instead of finding out when something breaks.

Low cost alternatives

The approach I have outlined above gives a great level of flexibility and scalability with a small upfront cost. However, there are other options out there if you are looking to create a website on a budget.

For example, you may pick an AI website builder and build your website entirely within that platform. This offers a simpler, all-in-one approach, although it can make it tricky to move your website elsewhere if you find it doesn't meet your needs in the future.

The best AI website builders start at around $2.99 a month, although this price will often rise to anywhere from $10 to $150 a month once the introductory period is over and depending on your website needs.

Organizations are investing heavily in artificial intelligence, but technology alone isn’t going to determine success. The businesses that unlock AI's full potential will be those that give governance the same attention as innovation.

In the rush to deploy AI tools, too many organizations are treating governance as something that can be addressed later. AI introduces a level of speed, autonomy and organizational impact that traditional governance frameworks were never designed to manage. Businesses that fail to rethink governance now risk increasing operational risk, slowing future adoption and undermining the value of their investments.

Organizations need to shift their mindset and recognize that implementing AI requires fundamental transformation in how decisions are made. With governance, accountability and transparency to be embedded from the outset, not pulled together after deployment.

AI is transforming organizations, not just technology

Unlike previous technology transformations, AI is influencing how decisions are made across almost every part of the business. From customer service and finance to human resources and operations, AI is becoming embedded in day-to-day processes and increasingly making recommendations, or decisions, with minimal human intervention.

As AI becomes more deeply integrated into business operations, responsibility can no longer sit solely with technology teams. Legal, privacy, risk, compliance and business leaders all have a role to play in ensuring AI is implemented responsibly and consistently.

Successful AI adoption is therefore as much an organizational and cultural shift as it is a technology transformation. Businesses that continue to treat AI as a standalone IT initiative risk fragmented ownership, inconsistent governance and missed opportunities to scale AI effectively.

Traditional governance wasn't built for AI

Many organizations still operate with a "deploy first, govern later" mindset, believing governance can be introduced once AI is established. The reality is that governance becomes significantly harder once AI is embedded across business processes.

Traditional governance models were built for a much slower pace of technology adoption. AI changes that equation. New tools, models and autonomous agents can be introduced into workflows in hours, while governance often still relies on manual reviews, siloed assessments and reactive oversight.

This creates a widening gap between AI innovation and organizational readiness. At the same time, AI is creating entirely new data use cases, while regulatory expectations continue to evolve. AI's use of data can also be dynamic and unpredictable, meaning documented controls are no longer sufficient when outcomes can't be predetermined.

Organizations need AI-ready governance – governance that evolves alongside AI through automated, collaborative assessments, programmatic controls embedded at the data layer, and continuous monitoring of risk across the business. As AI operates 24/7, governance must provide ongoing visibility into an organization's risk posture, rather than relying on point-in-time reviews.

The result is a growing disconnect between AI adoption and governance maturity. While organizations are investing heavily in AI, many have yet to modernize the governance, operating models and cross-functional accountability needed to support it. Closing this gap requires governance that operates at AI speed, enabling organizations to innovate with confidence while managing risk and maintaining trust.

Building the right foundations

One of the biggest misconceptions about AI governance is that it slows innovation. In reality, strong governance is what gives organizations the confidence to innovate, enabling them to deploy, scale and adapt AI responsibly.

The real shift isn’t purely technological or organization, it’s the combination of both. While AI is driving business transformation, organizations also need the right technical foundations to support it. AI can no longer be viewed as a technology initiative owned solely by IT.

Successfully scaling AI requires business leaders, risk teams and IT to work together, with IT embedding programmatic guardrails and controls that reflect business requirements. Without this partnership, organizational governance alone won't be able to keep pace with the speed and complexity of AI.

The organizations that gain the greatest competitive advantage won't necessarily be those that adopt AI first. They'll be the ones that recognize AI success depends as much on leadership, governance and organizational readiness as it does on the technology itself.

We've featured the best AI chatbot for business.

This article was produced as part of TechRadar Pro Perspectives, our channel to feature the best and brightest minds in the technology industry today.

The views expressed here are those of the author and are not necessarily those of TechRadarPro or Future plc. If you are interested in contributing find out more here: https://www.techradar.com/pro/perspectives-how-to-submit