New research from insurtech provider hyperexponential (hx) reveals that data ingestion is the most widely adopted AI use case in the insurance sector, with 95% of insurers in the UK and 89% in the US integrating the technology into their operations.
The findings are based on a survey of 350 professionals across underwriting, actuarial, and IT roles in the specialty and commercial insurance markets in both regions.
While adoption is high, the study highlights ongoing challenges in forming coherent AI strategies—particularly in the UK (see AI Promises to Revolutionize P&C Insurance).
A lack of designated leadership is contributing to fragmented efforts. According to the report, 41% of respondents indicated their organisation has no single person responsible for AI. This absence of oversight has made it difficult to coordinate AI activities across business units and regions.
Governance is another weak point. In the UK, only 18% of respondents say their organisation has clear and established governance and validation processes for AI.
In contrast, 45% of US insurers report having advanced frameworks in place, indicating a substantial gap between the two markets (see how Increasing Use of AI Technology Triggers Insurance Claims).
Despite more mature governance in the US, AI tools are frequently used outside of sanctioned programs.
Over 90% of US respondents reported the use of AI applications that were not formally implemented by their company—a trend commonly described as “shadow AI.”
This suggests strong interest from staff in applying AI to improve their work, but it also signals a disconnect between individual use and broader organisational strategy.
Amrit Santhirasenan, CEO of hyperexponential, stated that while it is encouraging to see high levels of AI adoption—especially in data ingestion—the lack of structured oversight creates risks.
He warned that without aligning experimentation with long-term objectives, insurers may face duplication of effort and reduced return on investment.
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.
Amrit Santhirasenan, CEO of hyperexponential
Santhirasenan stated that AI presents not only a technological opportunity, but also a leadership and governance challenge. He said insurers that treat AI as a strategic, organisation-wide priority will be better positioned to achieve meaningful outcomes.
