Market context and AI adoption
The session explored how AI is reshaping the insurance workforce against a backdrop of wider market disruption. EY described the current environment as a “NAVI” world: nonlinear, accelerated, volatile and interconnected. Insurance is being affected by sudden shifts in technology, regulation, demographics and customer expectations, while global volatility and interdependent risks are creating additional pressure on operating models.
AI adoption in insurance is still relatively early, but momentum is building. Many firms remain focused on generative AI tools, such as digital assistants, but the market is moving towards more agentic AI, where systems can autonomously execute multi-step tasks. Research cited in the session suggested that around 80% of firms are in the early stages of integrating AI into workflows, while many P&C carriers plan to allocate more than 10% of their technology budgets to AI over the next two years. However, EY cautioned that expectations of cost reduction may be ambitious and stressed that AI should not be viewed only as an expense-saving tool. In insurance, significant value may also come from improved underwriting, pricing, claims management and risk prevention.
Implications for roles and skills
The discussion highlighted that AI is a business and workforce issue, not simply a technology issue. Successful deployment requires governance, compliance, risk management, adoption planning, business-case development, process redesign and talent strategy. Poll responses suggested that most participating organisations are still at proof-of-concept or early adoption stages, though some are already seeing enterprise-wide use and value creation.
EY referenced World Economic Forum research showing that, by 2030, the fastest-growing skills in insurance are expected to include AI and data, cybersecurity and broader technology literacy. Skills gaps remain a major barrier to transformation, with upskilling becoming a priority for many insurers. The impact will vary by function. Claims, service, pricing and underwriting are expected to see significant change, while underwriting and actuarial roles may retain similar headcount in the short to medium term but require new skills. Finance and underwriting support may be more exposed to automation because of their operational and lower-value task profiles. Loss prevention, risk engineering, data and AI implementation roles may grow in importance.
Talent strategy and workforce priorities
The final part of the session focused on how insurers should respond. EY encouraged organisations to move from static role-based workforce planning towards skills- and capability-based planning. Talent strategy should be connected to business strategy and operating model design, covering workforce planning, capability needs, location, leadership, culture, sourcing and employee development.
HR was positioned as a critical partner in enabling AI adoption. This includes leading upskilling, embedding micro-learning into the flow of work, modernising learning and development, and helping employees use AI confidently and responsibly. EY warned that organisations that delay action may struggle to scale AI, lose talent to more technologically advanced competitors and face growing cost disadvantages. In future, insurers are expected to compete more on insight, speed, expertise and experience, supported by forward-looking, AI-enabled analysis. Workforce models will need to give employees more time for judgement, review, exception handling and guiding AI, while automating more manual and repetitive tasks.
