Insurance Leaders Face a Talent Crisis That AI Won't Solve
Aon CEO Greg Case is telling insurance executives something they don't want to hear: your AI strategy is incomplete without a people strategy, and the industry is building the wrong kind of foundation.
Speaking at a recent conference, Case said it plainly: "It is inconceivable that a winner in the application of AI isn't going to lead with a world-class people strategy."
The warning arrives as the insurance industry confronts two colliding forces. Job openings in finance and insurance fell to their lowest monthly level in a decade by December 2025, dropping from 281,000 annual openings to roughly 138,000 in a single month. At the same time, approximately half the US insurance workforce is expected to retire by 2038, creating more than 400,000 vacancies in roles that require deep institutional knowledge.
AI automation is eliminating the entry-level positions that have historically trained the next generation of underwriters, claims handlers, and other specialists. The industry risks hollowing out its talent pipeline just as it needs people most.
The underwriting problem
The tension is sharpest in underwriting. AI is rapidly absorbing the administrative tasks-data entry, loss run processing, motor vehicle record summaries-that served as training grounds for junior underwriters.
AXA XL's chief operating officer acknowledged the shift: "Historically, administrative work was how entry-level underwriters learned the fundamentals. Now we have to rethink how we develop talent."
Case argues that cutting early-career hiring in response to AI efficiency gains is backward thinking. "The idea that you would pull back on early careers-I'm dumbfounded by it," he said. "There should be opportunity here for everyone."
That stance puts Case at odds with major carriers. Chubb announced plans to cut up to 20% of its global workforce over three to four years as part of a digital transformation targeting underwriting administration, claims, and operational support. Allianz signaled cuts of 1,500 to 1,800 positions in its travel insurance operations.
Case's counterargument is not that efficiency is wrong, but that stopping there leaves the bigger prize untouched. "The winners are going to drive benefits from that standpoint, but they're going to drive growth, they're going to drive capability building," he said.
A skills gap inside the AI gap
Many carriers still run older core systems and lack the AI engineering and data science expertise needed to move beyond pilot programs. A 2024 survey found that 63% of senior managers in insurance believe a lack of digital skills is an issue in their workforce, with 30% calling it "a very serious issue."
Aon has spent roughly $1.3 billion on AI-related programs since 2023-what Case describes as the largest investment in professional services history. The lesson: technology spending without parallel investment in people fails to compound.
Aon's approach differs from the industry standard. Rather than using AI to reduce headcount, the firm aims to make its 60,000 employees dramatically more effective. "We don't want 30,000-we want 60,000 more effective," Case said.
Skills-based hiring as the new standard
More than one-quarter of insurance professionals today are over 55, while less than 25% are under 35. The pipeline is narrowing just as remaining roles demand broader skills.
Case argues the answer lies in replacing credential-driven hiring with continuous, skills-based recruitment. This means identifying what capabilities the business needs today and eighteen months from now, then building toward those targets through training, apprenticeships, and redeployment.
The hyperscalers already understand this. The fiercest competition in AI is not over data centers or compute power-it is over people. For insurers that struggle to compete on compensation with big tech, the differentiator becomes career development, skills investment, and meaningful work.
The pipeline risk no one is pricing
As entry-level roles contract, the pipeline of future experienced professionals risks collapsing. Roles most exposed to automation have historically served as first jobs for younger workers entering claims, underwriting, and customer service.
The roles that remain demand a different profile. AXA XL's COO described the challenge directly: "Underwriters and underwriting assistants will need to understand the rules behind the AI tools they use. They need to be able to interpret outputs from agentic AI, explain results, and make judgment calls that the technology cannot."
That is what Case is calling for at the enterprise level: treating talent development not as a cost to manage alongside AI investment, but as the strategic condition for AI investment to pay off at all.
For an industry that has spent three years debating how much AI will change the work, Case is reframing the question: Who will be equipped to do it?
Explore how AI strategy for executives must integrate with workforce planning and talent development for sustainable competitive advantage.
Your membership also unlocks:
