This piece is by Paul Donnelly, Global Head of Insurance, Version 1
The most important moment in the insurance customer journey comes when a claim is made. That is when customers find out whether their insurer will deliver on its promise. Often, claims happen during difficult moments that create stress and uncertainty, such as bereavement, serious illness or a road traffic accident.
That is relevant when we talk about artificial intelligence and its potential impact on the insurance industry, because insurers have always approached new technology carefully. Some people see that as reluctance, but it also reflects the responsibility insurers carry. They manage trust, sensitive personal data and decisions that can affect people’s financial security for many years.
AI has now reached a stage where it can support that responsibility in practical, proven ways. The opportunity for insurers is no longer about experimentation for its own sake. It is about applying AI to improve consistency, reduce friction, and help people achieve better outcomes.
Insurers’ caution has been justified
In its infancy, AI was often presented as a Swiss Army knife for every business problem. That framing was too simplistic, especially in insurance. Some challenges were, and still are, better solved through other technologies, while many tasks still need human judgement. In claims, empathy can be just as important as efficiency.
A customer submitting a routine health insurance expense usually wants speed. They want to upload a document, submit the claim and move on with their day. AI can help make that process smoother. A customer making a life insurance claim after the death of a loved one needs something different. They need reassurance. They need someone who can say, in effect: I understand, I can help, and I will take ownership of this for you.
Technology can support those interactions, but it cannot replace the human care required in moments of high emotion and show why insurance firms feel a deep responsibility to society. Life, health and income protection policies sit close to essential social infrastructure. When decisions affect vulnerable people, caution is part of doing the job properly.
The same applies to data. Life insurers may hold deeply personal information for decades, including medical history, financial details and family health information. In some cases, that data may relate to third parties, such as a sibling or parent mentioned during underwriting. Handling information of that sensitivity demands discipline. Insurers need to know that any technology used in underwriting, claims or customer service can be trusted, governed and explained.
From experimentation to practical value
The conversation around AI has changed because the technology and the ecosystem around it have matured. A few years ago, many AI initiatives were exploratory, with firms trying to understand where value might emerge. That period generated important learning, but it also produced plenty of proofs of concept that never progressed into operational use.
Insurers have little appetite for innovation for innovation’s sake. They want measurable outcomes, clear governance and confidence that investments will deliver value. Across the industry, AI is moving beyond experimentation and becoming a practical tool for improving efficiency, consistency in decision making and customer experience. Insurers are finding value in policy analysis, underwriting support, claims processing and customer service. Essentially, the areas where large volumes of information need to be reviewed quickly and accurately.
One of the most significant benefits is consistency. Human judgement remains essential, particularly when decisions have meaningful consequences for customers. At the same time, large organisations naturally experience variations in how information is interpreted and assessed. AI can help create greater consistency in the way data is analysed, and decisions are supported, contributing to fairer outcomes and a more predictable customer experience.
AI solutions can also help reduce friction in processes that have traditionally been slow and resource intensive. Applying for significant life insurance cover, for example, often involves extensive information gathering and assessment. Customers understand the need for rigour, but they also expect efficiency. AI can help insurers process and evaluate information more quickly while maintaining the oversight and controls such decisions require.
The same principle applies across the customer journey. Routine administrative interactions often benefit from speed and convenience, while more sensitive moments require human expertise and empathy. The most effective use of AI recognises that distinction and applies technology where it delivers genuine value for both insurers and customers.
For many organisations, this growing body of practical use cases is changing the conversation. Discussions that were once centred on possibility are increasingly focused on implementation and measurable business benefits.
Specialist support and ongoing innovation
Some insurers and reinsurers have created internal innovation labs to explore AI. That approach can work, particularly for organisations with the skills and appetite to invest over several years.
Many others will benefit from working with specialist partners that have already done much of the early learning. Version 1 was exploring AI at the point when the technology was still difficult to predict and commercially immature. That experience was valuable because it revealed what works and where the practical risks sit.
Those lessons now help insurers avoid wasted effort. They do not need to repeat every failed experiment or spend years stepping through unsuccessful proofs of concept. They can draw on established frameworks, methodologies and delivery experience that make adoption more predictable.
That matters in a sector where confidence and governance are essential. For insurers, the most useful AI partner understands the technology and fully appreciates the operating environment, the regulatory expectations and the importance of getting outcomes right.
A more confident phase of adoption
Insurance has taken a thoughtful approach to AI because the stakes are high. That approach has protected customers, supported trust and given the technology time to mature. Now the conditions are different.
AI is delivering measurable value in areas such as policy analysis, claims handling, underwriting support and operational efficiency. It can help insurers improve consistency, reduce delays and make better use of their data. It can also free people to focus on the parts of insurance where human expertise matters most.
The industry’s cautious approach is starting to pay off. Insurers are now better placed to adopt AI with purpose, confidence and clearer expectations of value. The opportunity ahead is not to use AI everywhere. It is to use it at the right opportunities, with stakeholders and customers at the heart of decision-making.
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