PwC Japan AI Panel at East Asia Insurance Conference

In the news: Japan: Japanese life insurer invests in US AI data centres: Life insurance major, Nippon Life will invest JPY2tn ($12.7bn) in various US AI infrastructure construction projects, reported the Nihon Keizai Shimbun. http://dlvr.it/TVbv0H Join: Lexgateway.com #Japan #AI #Investment #Insurance #DataCenters

AI can change who does the work. But perhaps the bigger question is: Who owns the outcome? Tomorrow. London. Lloyd's Market Association International Underwriting Association (IUA) #Insurance #AI #InsuranceTransformation #Leadership #LMA #IUA

The strategic new arenas reshaping insurance: AI is not the only significant driver of change for insurers: 18 high-growth industries present major new opportunities even as they reconfigure industry economics. http://dlvr.it/TVV6Qk

🤔 73% of insurance carriers now run AI in production. Only 7% have scaled it across the enterprise. That gap gets blamed on legacy systems, talent shortages, model quality - everything except the actual pattern in the data. Look at who's in the 7%. They aren't the carriers that moved fastest or governed least. Across three separate 2026 studies, the carriers that scaled AI are disproportionately the ones that built human oversight, explainability and audit trails into the initiative from the first sprint - not the ones that treated governance as something Risk adds before go-live. Singapore's MAS, Hong Kong's HKMA and Europe's EIOPA arrived at almost the same governance checklist independently, through completely different regulatory traditions. That's not three regulators slowing an industry down. That's three regulators converging on the actual precondition for an AI system anyone will trust enough to expand. The uncomfortable version of this: most stalled AI programmes aren't stuck because they moved too carefully. They're stuck because they moved fast on the model and treated oversight as paperwork - and paperwork doesn't survive contact with a board asking "who's accountable when it's wrong." 💬 If you're running a claims or underwriting AI initiative that impressed everyone in the demo and then went quiet for two quarters, that's usually where it happened. ⁉️ Where's your organisation actually stuck - the model, or the sign-off? Full analysis, with the data behind it. Link in comments. 👇 #AIGovernance #Insurance #GenAI #APACInsurance #ResponsibleAI #ClaimsAutomation #InsurTech #DigitalInsurance #sourceCode 

💡🤖 What could AI mean for the future of insurance? | https://lnkd.in/gJTUK6fA AXA Hong Kong and Macau and BytePlus are collaborating to develop AI capabilities tailored to insurance, with a focus on customer insights, operational support and content creation. The partnership aims to explore how AI can support more personalised and efficient insurance services. “We aim to co-innovate specialised, insurance-specific AI models that drive industry-wide transformation,” said David Ng, Deputy Chief Executive Officer of AXA Hong Kong & Macau. “We look forward to combining BytePlus's advanced AI solutions with AXA's deep knowledge to set new standards for AI innovation in the regional and global insurance market," said Elsa Wang, General Manager of BytePlus Hong Kong & Macau. #fintech #partnership #artificialintelligence

Beyond Insurance: How Japan and Europe Are Redefining Where and How to Play The insurance sector signals a deeper transformation—from financial protection to integrated life infrastructure. 1️⃣ Insurance is shifting from risk coverage to integrated life ecosystems: Insurers are moving beyond traditional protection models toward prevention, continuous engagement, and ecosystem-based services—embedding themselves into everyday life through healthcare, mobility, and wellbeing offerings. 2️⃣ Japan and Europe illustrate two distinct strategic paths: Japanese insurers are redefining where to play by expanding into adjacent service domains, while European insurers are redefining how to grow through capital-efficient models, asset management, and business model transformation. 3️⃣ The differentiator is decision architecture, not expansion alone: Sustainable success depends on who owns customer relationships, decisions, and outcomes—marking a broader shift from product-centric models to decision-driven systems across industries. #Insurance #Japan #Europe #Strategy #AI #ArtificialIntelligence

Everyday when I read the report my Agent (Rosemary, my librarian) sends me I find at least one article worth pondering upon. Today's report stopped me in my tracks. Beijing has outright rejected the slow down on AI, this comes after Trump ignored his AI oligarch's request for help and confirms that world leaders are determined to win this nonsensical race to superintelligence. An ambition that make have serious consequences for humanity. And then the Gartner predictions on AI which were made yesterday are really worth looking at. IT looks like Tokenomics is about to create some jobs and the insurers are about to get rich, or are at least going to start governing with premiums, well at least someone needs to make being reckless expensive! https://lnkd.in/dbrTyUvQ

The most important AI regulator may not be a regulator. Gartner's new strategic predictions include a very thought provoking : by 2030, insurers rather than regulators will drive AI governance, through underwriting standards for AI liability cover. It would not be the first time. Fire insurers wrote the first building codes. Marine underwriters set shipping standards long before any government did. In fact, you can read this as it unfolds in the Strait of Hormuz. Underwriters have always been the quiet regulators, because they are the ones who price the consequence. The distinction matters! It hits their pockets. A regulator asks whether you complied. An underwriter asks what it will cost them if you are wrong, and prices you accordingly. One of those conversations you can defer. The other arrives at renewal. Which turns AI governance from a compliance question into a commercial one. Not "are we conformant" but "what is this costing us in premium, and what would reduce it." For anyone in South Africa waiting on a national AI framework that is not expected before 2027, that is worth sitting with. Your insurer may get there first. So may your largest customer. A question I would genuinely like answered: Has anyone yet been asked an AI question during an insurance renewal or a broker review? If you have, share what they asked in the comments. https://lnkd.in/dUb3ZFwy #AIGovernance #AIRisk #Insurance #ResponsibleAI

AI holds considerable promise for APAC insurers, but the next phase of adoption will be defined by how effectively firms strengthen their data foundations, governance, and regulatory controls. Simon Smallcombe, Partner and APAC Insurance Lead at Capco, was featured in InsuranceAsia News discussing AI’s US$70 billion opportunity for insurers and the role responsible adoption can play in improving efficiency, enhancing decision-making, and helping address the protection gap. As AI becomes embedded across underwriting, claims, fraud detection, and customer engagement, insurers will need clearer visibility into where AI is being used, where risks may emerge, and where oversight should be prioritized. Capco helps insurers move from #AI opportunity to responsible scale. Developed by the Capco AI Studio in Hong Kong, Capco’s AI Risk Assessment Toolkit provides an enterprise-level view of AI governance maturity, risk exposure, and control priorities, helping insurers identify where stronger oversight is needed as AI adoption accelerates. The toolkit aligns with ISO/IEC 42001, the EU AI Act, MAS Project MindForge, SAFR, and HKIA GL8. The full article (paywalled): https://okt.to/5Qqw0O If you’d like to explore how Capco can support responsible AI scale in insurance, please reach out to Simon Smallcombe, Steven Nunez, Troy Barnes, CCXP #CapcoAIStudio #AIRiskAssessment #APACInsurance #AIGovernance #RiskManagement

AI IS MAKING INSURANCE ADMINISTRATION QUICKER But is faster actually more added value? A recent Deloitte analysis highlights a growing challenge: insurers are investing significantly in AI but often struggling to demonstrate where the financial return actually appears. That matters because productivity does not automatically become profit. If an underwriter, claims handler or operations team completes work more quickly, but the released capacity is simply absorbed, the business may become busier without becoming materially more valuable. The greater opportunity may lie beyond administrative savings: 1. better risk selection and pricing 2. reduced claims leakage 3. improved underwriting capacity 4. faster, better, informed decisions 5. stronger customer outcomes But value is only one part of a credible AI business case. Insurers should apply three tests: VALUE — Where does it land? Which measurable financial, operational or customer outcome will improve? CONTROL — Can you evidence it? Are ownership, data, decisions, monitoring and escalation clearly defined? RESILIENCE — Will it hold at scale? What happens when usage rises, model costs change, performance deteriorates or a critical provider becomes unavailable? An AI pilot can demonstrate impressive productivity while concealing weak economics, uncertain controls or new operational dependencies. At Luminary Diagnostics, we believe control should be built into the value calculation from the beginning—not considered after deployment. Boards should therefore move beyond and asking "where are we using AI?” The more valuable questions are: “Where will the value appear, how will we prove it, and can we sustain it under control?” The real AI return must be controlled, repeatable and sustainable. Which of these three tests presents the greatest challenge for your organisation? Source: Deloitte UK, “AI is expected to take cost out of insurance, but the industry is still finding it hard to prove value”, 4 September 2026. https://lnkd.in/ezXc_VZ7 #ArtificialIntelligence #Insurance #AIGovernance #DigitalTransformation #EmergingRisk