The customer journey is being remade by AI

The way customers interact with insurance from comparing coverage, premiums, navigating quoting journeys, how a claim is submitted, settled, and whether their loyalty is rewarded, is being reshaped by AI. The character of the relationship between an insurance organisation and customer is evolving into something different.

This is not a future scenario. One insurer indicated that it deployed over 150 machine learning models in claims alone, saving c£60 million in 2024. Another said it detected c£174 million of fraud in 2025. A third is understood to have insured one million previously excluded drivers, with a significant valuation and a profitable £0.5 billion revenue run rate

But most insurance organisations have not deliberately decided what their AI customer journey should be. The decisions are being made anyway, through individual model deployments, vendor procurement choices, productivity targets and third-party data feeds. The aggregate is reshaping the relationship in directions the board has not signed off.

Four moments of the AI customer journey

AI is now central to four moments where the customer experience is most consequential. These are organising categories chosen for where the AI-to-customer interaction is most material.

1. Becoming a customer

The customer needs cover. The customer searches, compares, receives a quote, decides whether to disclose what is asked. AI being used in pricing, eligibility filtering, quote generation, behavioural targeting, and aggregator-mediated discovery before any insurer's system is engaged.

2. Living with cover

The customer holds the policy. Data flows continuously through Telematics, app behaviour and third-party feeds. AI uses this data to price renewals, target cross-sell, score risk and identify vulnerability. Most of this is invisible to the customer.

3. The crisis

Something goes wrong. The customer claims, AI assesses, scores, triages, and sometimes settles. This is the moment that defines whether the cover was real, and where the customer is least able to negotiate.

4. Staying or leaving

The customer is approached for renewal or thinks about leaving. AI prices the renewal based on the customer's likelihood of accepting, not solely their risk. Loyalty is rewarded or penalised by the model's read of who is unlikely to switch.

This assumes a policyholder is engaged enough to notice data collection, demand explanations and challenge decisions. Many customers, particularly the elderly, financially vulnerable, non-UK citizens, the digitally excluded, and time-poor, are not.

Three possible end states

Across the four moments, the AI customer journey is producing three potential end states. Different firms are at different states for different moments, and firms may not sit cleanly in one

AI to the customer - Default	AI for the customer - Designed	AI with the customer - Involved

What is currently happening across UK insurers today.	A composite of best-practice patterns visible across UK firms.	The direction the combined regulatory framework appears to be heading.

AI to the customer (Default)

The journey is the result of AI being deployed piecemeal. Each component improves a metric. The aggregate is a customer relationship characterised by opacity, asymmetry and exclusion at the edges. This affects the c26% financially vulnerable uninsured in the UK as well as the £250 to £280 ethnicity premium gap. The automated claim rejection the customer cannot challenge. This state is not a failed implementation. It is the commercially optimal state. The asymmetry is profitable. The aggregate creates the regulatory and reputational exposurez.

AI for the customer (Designed)

The journey is the result of AI being deployed deliberately informed by a clear AI strategy. Choices made at board level, not in operational silos. Insurer A’s human-decides architecture in claims. Insurer B’s alternative-data inclusion in pricing. Explainability practices emerging in pilots. No firm exhibits Designed across all four moments. The Designed state is a composite of best-practice fragments that do not yet co-exist in any one firm. It is achievable but not yet operating end to end.

AI with the customer (Involved)

Here, the customer holds a real-time picture of what data is being used and can challenge any element. The right to human review under Data (Use and Access) Act 2025, is operationally real, not just stated. Consumer Duty is a design constraint, not a retrospective check. Senior Managers and Certification Regime (SM&CR) accountability is mapped and evidenced. Not yet implemented at scale by any UK insurer. We have inferred this direction as regulators have not published a 'customer Involved' view themselves.

What this means for Insurers

The question is not whether the customer journey is being reshaped by AI, but what kind of customer relationship insurers are consciously or unconsciously choosing to create. How does an insurer end up in the Default journey when nobody chose Default as a customer journey?

The answer is defined by three choices, made at every moment of the customer journey. These three choices could determine where a firm lands. This leads to some hard questions for example; at what point does pricing precision stop being actuarially justified and start being social sorting, and can you point to that boundary in your model; does your AI improve outcomes for consumers or improve extraction from them, and do you have a framework that can tell the difference at model level and which AI decisions is each member of your ExCo personally accountable for under SM&CR, and can they evidence oversight of those systems today?