UK insurers have moved beyond AI pilots, but many still struggle to scale execution, governance, and personalisation across daily operations, according to a new Earnix survey report. Earnix released Insurance 2026: Earnix AI Trends Bulletin.
The report found that 55% of UK insurers have already integrated AI into some business functions, showing a clear shift from experimentation toward operational use.
The UK report draws on the wider Earnix 2026 Industry Trends Report, based on insights from more than 400 global insurance executives. The regional analysis includes responses from 40 UK insurance leaders and compares local findings with global results.
The research examines how UK insurers embed, govern, and scale AI across pricing, underwriting, claims, and customer engagement workflows. The findings suggest that AI adoption has accelerated, but insurers now face a tougher problem: turning isolated use cases into consistent enterprise decisioning.
Earnix described this as the industry’s growing AI execution gap. The problem sits between ambition and repeatable operational delivery, especially when firms try to apply AI inside regulated, high-volume insurance decisions.
The report found that 98% of UK insurers already use, or plan to use, generative AI for processing unstructured data. That puts the UK market significantly ahead of the global average in one of AI’s most practical insurance applications.
Unstructured data remains a major operational burden for insurers. Claims documents, underwriting submissions, emails, broker notes, medical records, property reports, and policy correspondence still require large amounts of manual review.
UK insurers are also increasing their reliance on third-party data. The survey found that 91% of UK insurers plan to raise investment in external data sources, reflecting demand for better pricing accuracy, underwriting segmentation, claims triage, and customer analytics.
Regulation remains a constraint, though not a full stop. Earnix found that 53% of UK insurers say regulation moderately slows AI innovation, suggesting firms still need clearer governance structures before wider deployment becomes routine.
Personalisation remains one of the weaker areas in the market. The report found that 30% of UK insurers admit they significantly lag behind customer expectations around personalisation.
That gap matters because pricing, distribution, retention, and servicing increasingly depend on more accurate customer-level decisions. Insurers can collect more data than before, but many still cannot turn those signals into timely action across front-office and back-office systems.
The research also shows that UK insurers prioritise AI for operational workflows before customer retention use cases.
Claims processing and policy issuance rank ahead of retention, indicating that many firms first want to reduce friction inside high-volume administrative processes.
Adrian Mincher, head of UK, Ireland, and South Africa at Earnix, said UK insurers have clearly moved beyond isolated AI experiments. He said the pressure has shifted toward making AI work consistently inside pricing, underwriting, claims, and customer decision-making.
“What comes through strongly in this research is that the pressure has shifted to making AI work consistently in the real world – inside pricing, underwriting, claims and customer decision-making, where speed, governance and commercial performance all matter at the same time,” Mincher said.
The UK market has no shortage of ambition or investment. The harder task is turning insight into action at scale, especially when insurers need AI outputs to fit regulated workflows, commercial targets, and existing operating models.
He said the challenge appears most clearly in personalisation, where customer expectations are moving faster than many operational processes.
Insurers face pressure to deliver more relevant pricing, service, and communications without weakening governance or compliance controls.
The conversation around AI is becoming far more practical now – less about testing the technology, and more about whether insurers can bridge the execution gap, and actually embed AI confidently and at scale into the way decisions get made every day.
Adrian Mincher, head of UK, Ireland, and South Africa at Earnix
According to Beinsure analysts, the UK findings show a market moving from AI enthusiasm into implementation discipline. Insurers now need operating models that connect data, governance, pricing, underwriting, and customer workflows without creating new control gaps.
The winners will be the firms that make AI decisions auditable, scalable, and useful inside real insurance processes.
