Dive Brief:
- Insurers are becoming more confident in using AI, as companies mature in their AI investments and integrations, Evident Insights’ second annual AI Index for Insurance report found. The industry research firm tracks the 30 largest insurers in North America and Europe on their AI deployment and activity, talent and leadership.
- Talent was critical to success, the Evident report found. Insurers favored external hiring versus internal development programs, as projects shift from large-scale data pipeline construction to business-by-business AI integration and optimization.
- Claims management, internal process operations, underwriting, pricing and customer engagement topped the list of AI use cases, and three-quarters of respondents said productivity gains were the most reported positive outcome. “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.
Dive Insight:
Insurers, like most businesses, want to connect investments in AI to measurable financial value. More than four in five companies in the sector dedicate at least $5 million annually to AI, with 14% spending more than $50 million, according to an April report from agentic AI platform Simplifai.
Evident found that talent, innovation, leadership and transparency had the biggest effect on success.
Though much of the focus of AI adoption across industries has been on overall productivity and time savings, insurers can unlock value in more targeted ways. Small improvements in risk selection, underwriting and claims adjustment carry a disproportionate financial impact over efficiency gains in a business that earns up to 80% of its income from claims processing.
Productivity doesn’t provide a full view of AI maturity, according to the research.
“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 report’s co-authors said.
As investment strategies evolve, the talent needs of insurers are changing, with prominent roles shifting to orchestrating and managing AI outcomes.
In the last year, insurers pivoted to AI development and AI software implementation skills. Data engineering roles, which are often in demand in early and middle stages of infrastructure modernization initiatives, are shrinking — especially in organizations that build foundational capabilities from scratch.
As companies develop longer-standing AI projects, how they use the tools will affect their productivity. Evident linked productivity gains for insurers to three changes: moving from task-based AI to agentic applications; use cases that improve underwriting, pricing and claim outcomes; and a shift from point solutions to connected workflows.
“The most advanced insurers are therefore progressing on two tracks,” the report’s 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.”
