General Insurance Article - Over 90 percent of insurers embracing AI for data ingestion


The latest research from hyperexponential (hx), reveals that data ingestion is the most established AI use case across UK (95%) and US (89%) insurers, underlining the industry-wide progress in applying AI to core operations.

 However, the study, which surveyed 350 underwriting, actuarial, and IT professionals working in Specialty and Commercial insurance across the UK and US, also found that many insurers are still struggling to implement clear, coordinated AI strategies - particularly in the UK market.
 
 Leadership fragmentation and gaps in strategic clarity
 Insurers are taking varied approaches to AI leadership, with 41% of respondents saying there is no designated AI lead within their organisation. This fragmentation is creating challenges when it comes to delivering consistent AI strategies across departments and regions.
 
 AI governance is also a concern, with less than one-fifth (18%) of UK respondents say their AI validation and governance practices are “highly developed and widely communicated,” compared to nearly half (45%) in the US - underscoring a significant lag in structured AI implementation and oversight in the UK market.

 Shadow AI on the rise in the US
 Despite more robust strategic communication, many US insurers are still seeing AI adoption happen organically outside formal structures. Over 90% of US respondents report using AI tools that were not initiated by their organisation, indicating a rise in “shadow AI” as employees seek their own solutions to everyday tasks. This suggests a real appetite to test and utilise AI but also a potential disconnect between grassroots AI innovation and top-down governance, even in more advanced markets.
 
 Commenting on the survey findings, Amrit Santhirasenan, CEO of hyperexponential, said: "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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