The UK insurance industry, long known for its tradition and caution, today finds itself at an inflection point. AI heralds a step-change for tried-and-tested ways of working within insurance, posing challenges and opportunities.

In particular, the emergence of agentic AI systems, capable of executing repeatable tasks without human input, represents a significant opportunity for savvy organisations. But organisations must also be careful not to abandon their commitment to the values that define the insurance industry, namely, trust, precision and long-term thinking. In addition, upskilling teams to be confident and capable at using AI isn’t always as easy as it seems, creating the need for a long-term strategy that pivots businesses towards efficient and safe AI use.

So, let’s take a look at how AI can help transform insurance for the better, which hurdles businesses need to overcome and which strategies can ensure a successful, responsible transition.

Insurance as a strategic growth sector

Insurance has long been a cornerstone of the UK economy, contributing nearly £50b annually and underpinning countless other industries. Yet despite its strategic importance and the digital transformation that has spread across other areas of the financial sector, innovation in insurance has lagged. While banks embraced fintech post 2008, insurers focused on compliance and consolidation, with insurtech investment only surging in the late 2010s.

Now, there is a renewed sense of urgency. The London Market Group’s 2024 report warns that London’s growth is trailing international rivals. To maintain its global reputation, the market must innovate by developing new products for emerging risks like cyber threats and climate change. AI could be the catalyst for this innovation, enabling smarter underwriting and faster product development.

UK insurers embrace AI cautiously through pilot programmes

UK insurers are approaching AI with cautious optimism. Rather than rushing into full-scale AI rollouts, many are running pilot programmes and testing AI tools in controlled environments with human oversight.

In a typical pilot, AI may be asked to analyse commercial property submissions and suggest pricing or risk assessments. Human underwriters will then review these suggestions, providing feedback and corrections. Over time, this process helps refine the model, build trust among staff and identify shortcomings in the process.

This ‘human-in-the-loop’ model is essential, as it ensures that AI decisions are reviewed, validated and improved continuously. It also aligns with regulatory expectations around transparency and fairness. In a recent survey of global insurers by Goldman Sachs, the primary use case or consideration for adopting AI was to reduce operational costs with insurance risk underwriting second.

Balancing AI adoption and risk in insurance

Moving too fast or doing too little both present strategic risks for insurers. By trying to force ROI without sufficient human guidelines or review time, organisations unintentionally open the door to risks such as non-compliance, incorrect data protection and plagiarism or simply inaccurate information. All of this is in addition to the dangers of flawed AI data sets which may power biased models, encourage opaque decisions or misprice risks, leaving insurers at risk of financial losses, regulatory sanctions or reputational damage.

Yet, the risk of inaction is equally severe. Competitors, especially tech-savvy startups or overseas challengers, are already leveraging AI to offer faster quotes, personalised products and lower costs. By blocking AI altogether, insurers may find themselves outpaced by the competition.

The key to harnessing the benefits of AI without exposing your organisation to process and operational risks is to strike a balance. That involves finding ways of incorporating AI incrementally, with rigorous oversight, while investing in the skills, systems and culture needed to support it.

How UK insurers can transition to AI successfully

So what does a successful AI transition look like for UK insurers? We believe there are three key pillars:

• Cultural change: employers should position AI as a supportive tool, not a threat. Train staff to work confidently with AI and celebrate human-AI collaboration. AI is a continually evolving technology, so creating a failure-free culture of continuous learning is vital for teaching teams AI skills.
• Disciplined implementation: expand AI’s role only as fast as it proves itself. Use pilots to test, learn and build trust, and critically assess its outcomes to decide whether or not they are suitable and timesaving. Keep humans in the loop, especially for high-impact decisions.
• Industry collaboration: share best practices, avoid common pitfalls and develop shared standards for AI governance. The UK insurance market has a history of co-operation, and adopting AI should be no different.

As the sector embraces AI, it must do so in the right way. Insurance firms must move with the times and take advantage of new opportunities but without compromising their commitment to trust, fairness and resilience.

For more information on the future of AI in insurance, please contact Erin Sims.

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