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Third of UK insurers lag behind on personalisation as AI execution gap grows
30% of UK insurers lag in personalising customer experiences, despite 55% using AI in core operations. Earnix labels this the AI execution gap, as firms struggle to personalise.
A third of UK insurers admit they are significantly behind on personalising customer experiences, even as the industry pushes forward with artificial intelligence adoption. A new Earnix report, released 11 June, reveals that while 55% of UK insurers have integrated AI into core functions, many struggle to turn that capability into tailored customer interactions.
The "Insurance 2026: Earnix AI Trends Bulletin - UK Survey Results In Depth" draws on responses from 40 UK insurance leaders. It shows that 98% of UK insurers are using or planning to use generative AI for processing unstructured data - well ahead of the global average. But 30% say they are not meeting customer expectations on personalisation, exposing what Earnix calls the AI execution gap.
AI adoption accelerates
The survey data confirms AI is no longer experimental. Over half of UK insurers have embedded the technology into core business functions such as pricing, underwriting and claims. The UK's uptake of generative AI for unstructured data processing outpaces the global benchmark, signalling a market that is ready to invest.
Adrian Mincher, head of UK, Ireland and South Africa at Earnix, said: "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."
The personalisation gap
Despite the technology push, one in three insurers acknowledges falling short on personalisation. This gap is not simply a data or tools problem; it reflects the difficulty of translating analytical insights into real-time customer decisions. Regulation also plays a role: 53% of UK insurers said it moderately slows AI innovation. Meanwhile, 91% plan to increase investment in third-party data, a move that could help fill intelligence gaps but requires careful governance.
Mincher added: "UK insurers have clearly moved beyond experimenting with AI in isolated pilots. 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."
From pilots to production
Closing the execution gap means operationalising AI across decision workflows - not just building models. As firms work to embed these capabilities, targeted AI for Insurance training becomes a practical need for teams managing pricing, underwriting and claims.
Why this matters for insurance professionals
The shift from experimentation to daily use puts a premium on practitioners who can bridge data science and business operations. Professionals who understand how to apply AI outputs to refine pricing, speed up claims and personalise products will be central to their firm's ability to meet rising customer expectations. The data shows ambition is high; the next step is making it count in every customer interaction.