Insurers are shifting their AI hiring toward orchestration and software implementation skills as the industry moves beyond early infrastructure builds, according to Evident Insights' second annual AI Index for Insurance report released June 16. The report, which tracks the 30 largest insurers in North America and Europe, found that talent strategy is now a critical differentiator in turning AI investment into competitive advantage.
More than four in five insurers dedicate at least $5 million annually to AI, with 14% spending more than $50 million, according to a separate April report from Simplifai. Evident's research shows that companies are growing more confident in their AI deployments, but the way they build teams is changing fast.
Talent shifts from data engineering to AI orchestration
Insurers favored external hiring over internal development programs as projects moved from large-scale data pipeline construction to business-by-business AI integration. The most in-demand skills now center on AI development and software implementation, while data engineering roles are shrinking - especially in organizations that built foundational capabilities from scratch.
"The AI race in insurance is no longer about whether companies are investing - most are - but about whether those investments are compounding into real competitive advantage and business value," the report's co-authors said.
Productivity gains are not the full picture
Claims management, internal process operations, underwriting, pricing and customer engagement topped the list of AI for Insurance use cases. Three-quarters of respondents reported productivity gains as the most common positive outcome. But Evident's researchers warned that efficiency alone doesn't signal AI maturity.
"The more strategic test is whether AI can help insurers select better risks, price more accurately, manage claims more effectively, allocate capital more intelligently, and adapt faster as markets change," the co-authors said. Small improvements in risk selection, underwriting and claims adjustment carry a disproportionate financial impact in a business that earns up to 80% of its income from claims processing.
From point solutions to connected workflows
The most mature firms have pivoted from task-based AI to agentic applications and from point solutions to connected workflows. Evident linked productivity gains to three changes: moving to agentic applications, improving underwriting and claims outcomes, and integrating workflows across the business.
"The most advanced insurers are therefore progressing on two tracks," the co-authors said. "They are deploying AI where it can create measurable value today, while investing in the less visible foundations needed to support broader integration over time."
Leadership and transparency also had a measurable effect on success. The AI for Executives & Strategy challenge, the report suggests, is to guide these parallel efforts without letting short-term efficiency metrics overshadow long-term structural advantages.
Why this matters for insurance professionals
The shift from data engineering to AI orchestration means roles are changing. Insurance professionals who can manage AI outcomes, connect tools across underwriting and claims workflows, and measure improvements beyond simple productivity will be in high demand. In a sector where a 1% improvement in loss ratio can dwarf office efficiency gains, the ability to link AI to core financial metrics is the skill that separates leaders from the rest.
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