Insurance professionals, women most at risk from AI

A new report should serve as a wake-up call for every brokerage boss and human resources director operating within the UK insurance market. While artificial intelligence is frequently lauded in boardrooms across the City as a silver bullet for operational inefficiency, the human cost at the transactional level is being dangerously ignored.

Recent findings published by the Brookings Institution expose a critical vulnerability at the heart of the modern workforce. On average, highly AI-exposed workers appear well-equipped to handle job transitions relative to the rest of the workforce, yet a staggering 6.1 million workers in the US still face both high exposure and low adaptive capacity.

Significant uncertainty surrounds the question of how AI will impact labour markets, and occupation-level measures cannot tell the whole story. However, adaptability analysis can help reveal who may be most in need of support to weather AI-driven job transitions.

For the British insurance sector, this warning sounds the alarm for our sales agents, claims handlers, and administrative support staff. When a role relies heavily on routine, codifiable tasks - such as basic quoting, data entry, and standard policy renewals - generative AI can readily absorb it. If brokerages allow these roles to simply evaporate without proactive intervention, they risk haemorrhaging loyal staff who possess years of invaluable institutional knowledge and client goodwill.

Here is how forward-thinking brokerages can build internal mobility pathways to transition vulnerable agents into high-value, AI-proof roles:

1. Pivot from quoting to complex risk advisory. AI is exceptional at crunching numbers, aggregating data, and generating standard policy options. What it entirely lacks is empathy, nuance, and the ability to negotiate complex, multi-line risk during a crisis. The first step in internal mobility is shifting agents away from high-volume transactional sales. Upskill them in complex commercial lines, specialty risk, or high-net-worth advisory. Train your people to interpret the AI's output, contextualise it for the client, and build the deep relationships that algorithms simply cannot replicate.
2. Establish 'bridge' roles. One cannot expect a junior agent to leap from basic data processing to a senior advisory position overnight. Create transitional bridge roles - such as 'client success associate' or 'risk analyst trainee' - that allow administrative and sales staff to shadow senior brokers. This provides a secure, structured environment to develop the high-level critical thinking, business acumen, and negotiation skills required to thrive in the London Market.
3. Audit and subsidise adaptive capacity. Low adaptive capacity often stems from a lack of financial buffer to take time off for retraining, or a lack of access to elite educational networks. Brokerages must step in to close this gap. Offer fully subsidised, on-the-clock training for advanced industry certifications, such as the Chartered Insurance Institute (CII) qualifications. When you invest in your team's adaptive capacity, you transform a vulnerable worker into a fiercely loyal, highly skilled asset.

The road ahead

As the global insurance community prepares to convene at InsuranceFest on the Santa Monica Pier this July, this conversation must feature prominently on the agenda. We can no longer afford to view AI simply as a mechanism to trim overheads.

The brokerages that dominate the coming decade will not necessarily be those with the most expensive proprietary algorithms; they will be the ones that successfully bridge the gap between their technology and their people, ensuring their most loyal employees are elevated, not eliminated, by the AI transition.