Why AI is the missing piece in a fractured claims experience

In a market of instant comparison sites, a sluggish insurance claim is an open door to churn. What should be a moment of reassurance too often becomes a test of endurance, exposing long-standing weaknesses in insurance claims processes.

Data from Accenture shows that 31 per cent of claimants are not fully satisfied with their most recent claims experience. It is this dissatisfaction that puts approximately $170 billion in insurance premiums at risk.

The insurance industry is unusual in that the product is visible in the terms and conditions of the policy, but the customer experience is unknown until something goes wrong. That first claim is therefore the sector’s moment of truth. For digital-first consumers, tolerance for friction is practically zero. A clumsy process or slow payout can erase years of brand investment in a matter of hours.

Mapping the friction points in claims

While claims processing remains at the core of the insurance industry, it remains one of the most resource-intensive and customer-sensitive processes. While most insurers know where their pain sits, brittle technology makes action to rectify these operational challenges far from easy.

Research shows that 80 per cent of insurers do not handle high-severity claims effectively. While poor training and escalation processes may be significant factors, there is still a heavy reliance on outdated technology 74 per cent of insurance companies depend on legacy systems. Using systems that lack data integration and automation can lead to delays, high operational costs, and subpar customer experiences under patchwork workflows.

Outdated processes not only prevent insurers from modernising the claims experience, they also limit the wider transformation that could unlock the sector’s full potential. But we are talking about a sector where the product is 100 per cent defined in the terms and conditions. This makes insurance a hotbed for AI innovation – one ‘claim-makers’ stand to gain.

Turning AI theory into a better claims reality

While some in the industry chase abstract promises of AI-driven transformation, others are already putting real tools to work. Practical AI is the combination of skills and workflows used to make AI accessible and beneficial to non-technical knowledge workers.

Deployed well, they triage claims, extract data from photos, and draft clear explanations while leaving nuanced decisions to people. The goal is not science-fiction general intelligence but narrowly focused models that excel at specific tasks.

Take Revolut, for example. By embedding an AI assistant into its everyday purchase protection workflow, the company’s digital claims solution analyses data to offer recommendations to claim handlers and enables policyholders to submit claims faster through pre-filled fields.

The result was a threefold improvement in handling speed and shorter resolution times for 66 per cent of claims.

An agentic force comes next

The next leap is agentic platforms – AI systems able to learn, decide, and act across the workflow. Gartner expects a third of enterprise software to include agentic components by 2028, and early pilots show dramatic efficiency gains: these systems validate policy status, check fraud signals, propose reserves, and trigger payment, escalating only when rules are breached.

Adoption, however, remains sparse. According to the Financial Conduct Authority, 75 per cent of UK financial institutions are currently exploring AI solutions, but fully autonomous use cases remain rare, accounting for just 2 per cent of implementations.

Executives worry about governance, regulators demand transparency, and boards cannot accept black boxes. Yet modern design pairs explainable AI with auditable trails, providing both speed and control. It is, after all, a sector where the product is 100 per cent defined in the terms and conditions.

Insurance companies that act now can expect to cut settlement times from days to minutes, make proactive, thoughtful customer outreach a standard practice, and enhance empathy by surfacing the right data at the right moment. Agentic systems let front-line teams spend more time listening and less time copying information between screens, and when a storm hits, the same architecture scales effortlessly, handling surges without degrading service.

Yet adoption is uneven, and competitors that hesitate turn every claim into a recruitment ad for someone else. With sound governance and a sharp focus on customer needs, insurers can set the benchmark for the next generation of services. Because innovation is optional until your customers leave; then it’s too late.

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