hyperexponential research highlights differences in AI strategy and governance between UK and US insurers

New findings from Insurtech provider hyperexponential (hx) show that data ingestion is the most commonly adopted AI application in the insurance sector, with 95% of UK and 89% of US insurers incorporating it into their operations.

The study, which surveyed 350 professionals in underwriting, actuarial, and IT roles across the Specialty and Commercial insurance markets in the UK and US, also uncovered persistent difficulties in building clear and consistent AI strategies—challenges that are particularly evident in the UK.

Approaches to AI oversight vary widely, with 41% of respondents saying their organisation has no designated point person responsible for AI. This lack of structure is making it difficult to ensure coordinated efforts across departments and markets.

Governance remains a weak spot as well. In the UK, only 18% of those surveyed say their AI governance and validation processes are well-established and clearly communicated. That figure rises significantly in the US, where 45% describe their practices as advanced—highlighting a notable divide in how structured AI efforts are between the two regions.

Even with more robust frameworks in place, many US insurers are seeing AI tools used outside of official programs. More than 90% of US respondents report using AI applications that were not formally introduced by their company.

This trend toward unofficial adoption—often referred to as “shadow AI”—suggests employees are eager to apply AI to improve their work, but it also reflects a disconnect between individual experimentation and organisational strategy.

While enthusiasm for AI is strong, many insurers still face the challenge of bridging informal use with coordinated, well-managed implementation.

Amrit Santhirasenan, CEO of hyperexponential, commented: “It’s encouraging to see insurers embedding AI into their operations, especially around data ingestion, which is a vital step towards truly intelligent automation. However, implementation without thoughtful, proportional oversight creates risk. Without a clear strategy that links experimentation with long-term goals, organisations could end up repeating work or missing out on the full benefits of AI.”

“The message is clear – AI is not just a technological opportunity and challenge. It’s a leadership, governance, and cultural challenge, and the insurers who succeed will be those who treat it as a company-wide objective, not just a department-led experiment.”

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