As AI tools become more embedded within financial services, moving from strategic ambition to operational reality, the insurance and protection sector is evaluating how these technologies fit into long-term operating models.
With the focus now being on practical implementation, we bring together perspectives from across the insurance and protection profession, each addressing a single, focused question: Where can AI deliver real value in the insurance and protection sector? Their perspectives offer a snapshot of how the market is assessing AI’s current contribution, and its longer-term potential.
Ian Douglas, head of architecture at Guardian comments:
“AI delivers real value in insurance and protection when it genuinely helps us serve advisers and customers better, making things clearer, faster and more personal – not more complicated.
Right now, one of the most practical uses is simply helping us handle information more effectively. AI can summarise documents and pull together material from multiple sources to create new content. The real opportunity, though, is using those same tools to personalise communications. Insurance can feel complex and abstract, so being able to present information in ways that feel clearer and more relevant to each customer makes a real difference to engagement and understanding.
We’re also seeing strong benefits from conversational tools. AI-powered chat systems can respond to adviser and customer questions in straightforward language, helping to explain product features or policy terms without jargon. We’re exploring AI as a real-time translation aid too, so our teams can communicate more easily with customers whose first language isn’t English.
Accuracy is another area where AI is proving useful. By analysing information from different sources, it can flag inconsistencies – for example, between what’s shared during an application and any supporting evidence. AI helps us spot potential issues or gaps early, to ensure customers get the cover they need and to minimise problems later if they need to claim. We’re currently testing AI to support post-issue compliance checks, not to replace human judgment, but to build in additional safeguards.
Looking ahead, there’s growing potential for AI to act as an early-warning system, continuously scanning transactions and processes to detect unusual patterns and to identify emerging risks. The aim always is to protect customers but also to innovate as needs evolve.”
John Underwood, director of technology at Cirencester Friendly:
“In an admin-heavy sector like ours, using AI to carry out repetitive work has the power to free up the peoples’ time. It will allow us to think more creatively, and indeed objectively, about how we can best use AI in the future. This is likely to further drive genuine real-world adoption within our sector and hopefully drive fresh innovations.
Currently, there is a lot of hype, but a low conversion of AI finding its way into production. Now is the time to begin shaping more productive outcomes.
The sector is awash with data of all kinds, so focusing AI to help advisers make sense of it, providing them with actionable insights which help them make the right recommendations for their customers, must be at the forefront of the solutions providers deliver.
We want to use technology to complement the skills of our intermediaries rather than find ways to replace them, and our roadmap is geared to helping advisers better understand our underwriting processes and product particulars.”
Jonathan Sandell, CEO at Shepherds Friendly:
“There are multiple areas within the insurance value chain where AI has the potential to deliver significant value, but the two we are most optimistic about in the near term are claims and underwriting. This is because of their potential to benefit not just providers in the space, but most importantly, their customers.
When it comes to claims, AI can help speed up and capture claims submissions by reviewing medical evidence, checking for coverage, providing summaries and screening for fraud and misrepresentation. This means claims professionals are not spending time on lower-value claims administration, freeing them up to focus on complex and sensitive cases. In doing so, their role shifts away from chasing paperwork and towards providing empathetic support to claimants.
In the underwriting process, we believe AI has the potential to separate low-risk cases from those that require the decision-making skills of experienced underwriters. It could validate much of the medical data to reduce the reliance on GP reports, as well as allow for enhanced risk selection. Eventually, we hope it will allow the industry to move away from standardised loading and broad exclusions towards more refined risk assessments that are more aligned to actual risk.”
Cameron Erskine, wealth management consultant and Financial Adviser at SeventySeven Wealth Management:
“AI is reshaping the way we work and protect clients – not by replacing advisers, but by exposing and correcting inefficiencies. We are a far stretch away from AI replacing the value that we provide to our clients, but there are several cases in which it can provide amplification to the work we already do.
AI can act as a research assistant, providing instant access to seemingly infinite knowledge, allowing you to quickly become an expert on any topic. It can also support with compliance and copywriting, drafting suitability reports or summarising fact-finds into structured insights. It can also enhance client communications by refining messaging and translating industry jargon into clear, client-friendly language. Beyond client-facing uses, AI can improve the efficiency of a business through identifying opportunities for optimisation, building internal knowledge bases, and supporting performance analytics to highlight operational gaps and opportunities for development.
The potential benefits that can be delivered can only be realised once AI has been implemented. Clear boundaries and robust oversight are essential; data must be secure, usage policies clear and abided by, and outputs reviewed before forming part of advice – accountability must sit with the firm. Firms that implement AI as a tool, rather than a shortcut, will see both productivity and client trust strengthen.”
Kesh Thukaram, Co-Founder, Best Insurance and excitare.ai , comments:
“Where AI can deliver real value is by giving customers what they actually want. As an industry, we have a tendency to design “bells and whistles” products with added features and benefits because we believe this adds more value.
But the truth is, most customers don’t care about this stuff; they just want insurance that’s affordable and convenient. They want a specific risk covered at the lowest possible price, and they want to be able to buy it easily, quickly and without any level of complexity. No one wants to spend more than a few minutes thinking about insurance.
This is where AI, particularly generative AI, plays a vital role. Instead of building one-size-fits-all products loaded with low-usage add-ons, generative AI can help insurers strip back products to their core purpose and personalise them to the needs of each individual.
This concept is known as hyper-personalisation and allows insurers to use data-driven insights to create target benefits based on individual preferences, rather than creating standardised products with add-on features that customers don’t use or want.
Using generative AI can help insurers streamline the customer journey and make insurance products more accessible, affordable and relevant, leading to improved levels of take-up.”
Robert Morrison, Chief Underwriting Officer at Aviva:
“AI is transforming efficiency in the protection insurance sector, and Aviva is at the forefront. We’ve launched the industry’s first AI underwriting summarisation tool, making the review of medical evidence for life insurance easier and faster.
We’ve found that AI can dramatically reduce the time underwriters spend reviewing lengthy medical documentation. In life insurance underwriting, medical reports can exceed 90 pages, making manual review from underwriters slow and time consuming.
Aviva’s AI summarisation tool uses generative AI to analyse these extensive digital reports, seeing a c90% reduction in the volume of data, thus filtering out irrelevant details and highlighting the key clinical information underwriters need. This allows underwriters to work more efficiently while maintaining accuracy and care.
We see AI in the protection sector as an enabler, allowing colleagues to work more efficiently. Since launch, it has markedly approved the time it takes for our underwriters to make a decision on life cover applications.”
Anna Rogers, LV= Head of Underwriting, said:
“Underwriting is a core function of the protection insurance sector, enabling accurate risk assessment and appropriate pricing. While historically reliant on manual processes, the field has advanced significantly through automation, digital tools and improved data accessibility.
Skilled underwriters remain essential to ensuring quality, fairness and customer trust in underwriting. Machine learning and predictive analytics through the use of AI (Artificial Intelligence) can process complex medical and lifestyle information accurately and at speed, supporting more consistent and efficient decision-making. These capabilities enhance risk evaluation while allowing underwriting teams to focus on nuanced judgements and good customer outcomes.
At LV=, we are committed to updating the underwriting experience without compromising the human aspect. Automation can deliver greater speed and simplicity, but it cannot replace empathy or professional judgement. We’re focused on integrating AI thoughtfully, in ways that add genuine value to customers and advisers. Our goal is to increase underwriting capacity and reduce turnaround times while maintaining strong oversight, fairness and accuracy.
Looking ahead, we expect underwriting to increasingly blend AI capabilities with human expertise.”
