Insurance professionals, women most at risk from AI

MLC this week. Atlassian last week. Block the week before. The drumbeat of corporate restructuring is growing louder across Australia, and the underlying catalyst is increasingly clear: the integration of artificial intelligence. In fact, every single tech company layoff this year (at least 4,450) has been blamed on AI.  AI is already reshaping the insurance sector, but whose jobs are actually at risk? And if automation comes for your role, will you be able to adapt and reskill?

The answer is, of course: It depends.

As AI adoption accelerates, insurance brokerages and underwriting agencies face a stark reality. Calculating which jobs will be automated is no longer enough. The true measure of workforce resilience lies in a worker’s capacity to adapt, and new data reveals a severe gender divide among those most at risk.

A report by the Brookings Institution, titled Measuring US workers' capacity to adapt to AI-driven job displacement, offers crucial insights that parallel the Australian labour market. It warns that relying solely on AI exposure metrics fails to account for a worker's actual ability to navigate a shifting landscape. Instead, workforce planners must measure "adaptive capacity" alongside technical exposure to understand the true impact of automation.

The findings present a complex picture for HR professionals and agency principals. On average, highly AI-exposed workers appear well-equipped to handle job transitions relative to the rest of the workforce. These individuals often possess the transferable skills, financial buffers, and geographic mobility needed to pivot.

However, the report highlights a critical vulnerability: millions of workers still face both high exposure and low adaptive capacity.

While the Brookings summary notes that occupation-level measures cannot tell the whole story and that significant uncertainty surrounds the question of how AI will impact labour markets, a deeper analysis of the demographic data paints a highly concerning picture for gender equality in the workplace.

The gender penalty in the AI transition

When analysing whether women are more likely than men to lose jobs to AI, the broader data points to a resounding yes. According to expanded demographic data from the Brookings research, a staggering 86 per cent of the highly exposed and least adaptable workers are women.

This disparity is largely driven by occupational segregation. Female-dominated occupations are almost twice as likely to be exposed to generative AI as male-dominated ones.

Within the insurance sector, women remain heavily concentrated in clerical, administrative, and business support roles—such as claims processing clerks, receptionists, and accounting assistants. These positions rely heavily on routine, rule-based, and digitised tasks that generative AI can readily absorb. Conversely, male-dominated fields involve physical or non-routine tasks that are currently much harder to automate.

Furthermore, women are largely locked out of the new opportunities AI is creating, comprising only about 30 per cent of the global AI workforce. This means women are facing higher rates of displacement while simultaneously lacking the pathways to transition into the tech-centric roles replacing them.

The mandate for insurance leaders

For industry leaders across Australia, this data demands a strategic pivot. As the sector prepares to debate the future of broking, underwriting, and risk management at major B2B gatherings like InsuranceFest on the Santa Monica Pier this July, the conversation must move beyond simply identifying which jobs will disappear.

Adaptability analysis can help reveal who may be most in need of support to weather AI-driven job transitions. Rather than applying blanket upskilling programmes across the board, HR departments and agency heads must identify the hidden pockets of vulnerability within their own organisations. Support structures-such as targeted retraining, internal mobility pathways, and financial transition assistance-must be directed toward the administrative staff and sales agents who lack the inherent adaptive capacity of their executive or technical peers.

The AI revolution is not entering a neutral labour market. If insurance leaders fail to proactively manage this transition, the integration of AI risks reversing decades of progress in workplace gender equality.

Who is most at risk?

According to the report's expanded data, here are the specific occupations highlighted as being the most highly vulnerable, along with their low adaptive capacity scores:

• Office clerks, general (22% adaptive capacity)
• Medical secretaries and administrative assistants (23% adaptive capacity)
• Insurance sales agents (24% adaptive capacity)
• Interpreters and translators (29% adaptive capacity)

Conversely, roles like software developers, financial managers, and lawyers also have high AI exposure, but boast adaptive capacity scores in the 96% to 97% range because those workers generally have the resources, networks, and advanced skills to successfully weather the transition.

So what can we do to lessen the impact?

Here is how forward-thinking brokerages can build internal mobility pathways to transition vulnerable sales 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 your 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 cannot replicate.
2. Establish 'bridge' roles. You cannot expect an agent to jump from basic data processing to a senior advisory role overnight. Create transitional bridge roles - such as 'client success associate' or 'risk analyst trainee’ - that allow administrative and sales staff to shadow your senior brokers. This provides a secure, structured environment to develop the high-level critical thinking, business acumen, and negotiation skills required for the future of the industry.
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 (like ANZIIF qualifications or specific risk management diplomas). 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 we prepare to gather the industry's top executives, innovators, and risk managers at InsuranceFest on the Santa Monica Pier this July, this conversation must take centre stage. We can no longer afford to view AI simply as a mechanism to trim overhead.

The brokerages that dominate the next decade won't necessarily be the ones 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.