Insurance Industry Faces Talent Crisis as AI Reshapes Entry-Level Work
Insurance employers are hiring for skills that didn't exist five years ago. A new analysis of 170,000 completed courses and 10,000 earned designations in 2025 shows the workforce is making deliberate shifts in professional development-and they're doing it out of necessity.
The US Bureau of Labor Statistics projects 400,000 insurance workers will retire by 2026. Simultaneously, AI is automating the entry-level roles that once fed the industry's talent pipeline. The result: demand has pivoted sharply toward technical proficiency.
What employers actually want to hire
Ninety-one percent of insurance and pension fund employers now plan to hire people skilled in working with AI. That figure towers over the global average of 62%, according to The Institutes Knowledge Group's 2026 Skills Report.
But technical skills alone won't cut it. Employers are placing greater weight on soft skills-strategic thinking, communication, adaptability. As automation handles routine work, human judgment becomes the differentiator between competent staff and future leaders.
The tension is already visible in underwriting. Nearly half of underwriting executives now use AI in their work, yet around 70% worry about long-term talent availability. Their top concern: an aging workforce and loss of institutional knowledge, cited by 38% of respondents. Another 20% flagged the challenge of balancing automation with human expertise.
How companies are retaining people through transformation
Aviva deployed 80 AI models across claims operations without cutting headcount. Instead, the company shifted adjusters away from routine data assembly toward complex cases requiring human judgment. Employee engagement scores more than doubled.
The pattern works because it addresses what professionals actually need: clear pathways from entry-level work to leadership roles. Organizations can build these by combining early-career interests with longer-term business needs, setting baseline skills early to widen the candidate pool.
How people learn matters as much as what they learn
Simulation-based, experiential learning produces better knowledge retention and on-the-job skill application than traditional methods, according to research cited in the report. Professionals perform better when training mirrors real conditions-when they can work through realistic scenarios in consequence-free environments.
The shift underway in insurance isn't about replacing workers with machines. It's about redefining what work means. Those who build skills in AI for insurance operations-and develop the judgment to know when to apply them-will have the most stable career paths ahead.
Your membership also unlocks:
