AI's Wake-Up Call: Reinventing Insurance and Wealth Management Business Models

Recent AI launches have jolted insurers and wealth managers. For example, Insurify's AI-powered comparison app and Altruist's 'Hazel' planning engine, both of which highlight how rapidly advancing AI tools are pressuring sector economics. While some viewed the market response as an overreaction, it was nevertheless immediate. Several UK wealth managers saw sharp share-price declines as investors responded negatively to the potential for AI-driven disintermediation. Insurance brokers were similarly affected, reflecting concerns about price-comparison models in a world where AI can quickly and accurately scan quotes and policy language.
 

None of this should come as a surprise

UK insurance and wealth management institutions are already looking at scaling AI, particularly in operations and back-office functions, where the spotlight remains on efficiency, across servicing, fulfilment, underwriting and claims automation. Yet progress remains uneven, with more mature insurers pushing ahead with full scale deployments this year, while others remain mired in pilot stagnation. 

The longer-term disruptive risks and opportunities of AI have been clear for some time. Over the past 18 months, AI technology players have accelerated towards agentic systems, capable of taking multistep actions, orchestrating data from multiple sources and collaborating with other agents to complete tasks end-to-end. This pattern is visible across sectors (e.g., in legal and research process automation, as well as embedded agents in areas such as client servicing and underwriting to boost productivity) and is increasingly reshaping expectations. 

Recent market moves have demonstrated investors’ sensitivity to how rapidly AI tools could reshape established business models. While the near-term reaction has been sharp and could be a blip, the longer-term message is that all firms operating in the insurance and wealth value chains need to consider how best to make use of these technologies, to not only improve efficiency but rethink how products and advice are distributed.
 

Automation at scale, with humans in the loop

So how will these developments play out? Uncertainty is still high, but there are at least two plausible futures:

On one hand, AI could drive large-scale disintermediation in advice and insurance distribution. In wealth, autonomous agents may soon handle single-portfolio views, though truly holistic planning may require a bit more time. In insurance, AI-enabled personal agents may become more attractive to consumers than today’s broker-led channels and comparison platforms. In the same way, over the near term, increasingly automated, AI-supported journeys will likely compress servicing, research, recommendation and transaction flows into more agent-led processes. In this world, incumbents would face intensifying margin pressure as servicing becomes materially cheaper to deliver, opening the door to mass-market financial planning at previously unachievable price points. 

On the other hand, increasing use of AI could improve the customer experience while reducing the need for contact, streamlining routine interactions and increasing personalisation. In the future, AI may play a key role in serving customers with complex needs, vulnerabilities or in those moments that matter in a customer's life. There may also be a greater premium placed on human interaction across advice and distribution, as customers look to their advisors to contextualise decisions, provide reassurance and offer sound, strategic judgement. These moments will still be deeply AI-enabled behind the scenes, augmented with automated analysis and personalised insights. However, in this scenario, AI becomes a force multiplier rather than a substitute.

And, of course, both scenarios may play out simultaneously, coexisting across product and customer segments.
 

Time to re-imagine the business model

The future will not wait, and institutions that are still entangled in legacy data, regulatory complexity, fragmented platforms and uncertain digital transformation strategies risk falling behind the pack, losing relevance and share to more forward-looking competitors. The window for fixing the foundations of such organisations is narrowing, and the era of incremental improvements is over. By 2030, the gap between AI-enabled players and their digitally immature competitors will widen considerably. Those who fail to invest sufficiently in data infrastructure and AI integration across their operating models – from underwriting to customer service – risk diminishing relevance as their competitors compound their AI-driven advantage. 

For many insurers and wealth managers, the primary focus remains on operational efficiency, while others are still laying their digital foundations. But efficiency alone will not be enough. The winners in this AI race will be those who use this moment to reinvent their business models around these technologies, redefining distribution, advice and operational performance.