Insurers are leaving AI's biggest financial gains on the table by keeping the technology stuck in isolated pilot projects, according to McKinsey & Company. Distribution costs are consuming as much as $0.80 of every first-year life premium, and the gap between premium growth and profitability points to weak operating efficiency across the industry.
Global gross written premiums have grown 4.9% a year since 2005 to about $8.3 trillion in 2025, while profits before tax increased just 4.3% annually to roughly $580 billion, McKinsey said in a July report. Premiums as a share of global economic output have stayed flat for a decade, even as the natural catastrophe protection gap reached $133 billion in 2025 and less than 1% of global cyber costs were insured.
Commissions account for $0.10 to $0.25 of every premium dollar in property and casualty insurance, and insurance cost ratios are 17% higher globally than in 2005.
The alignment gap
NTT Data Group Corporation surveyed 291 insurance executives and classified 46, or 16%, as AI leaders. The difference between leaders and laggards comes down to strategy: 85.8% of insurers whose AI strategies were fully aligned with their business strategies reported profit increases of at least 5% from AI, compared with 45.5% of insurers with less-aligned strategies.
AI leaders are also spending more. About 71.7% described their AI investment as "very significant," compared with 51% of lagging insurers, and 63% planned to increase spending further.
"The real question for insurers isn't whether to invest in AI; it's how to embed it into underwriting, claims and growth in a way that's governed, scalable, and built to last," Bruno Abril, NTT Data's global lead for the insurance industry, said in a June report.
Where AI is already paying off
McKinsey said AI could reshape how insurers sell and service policies, including through AI assistants that compare coverage and switch policies on behalf of customers. The technology has already reduced onboarding costs by as much as 40% and increased agent productivity by 10% to 20%.
More than half of AI leaders are rebuilding core underwriting, claims, and policy systems with AI embedded into them, compared with 6.5% of lagging insurers. For insurers looking to build these capabilities, AI for Insurance training covers the practical applications in claims processing, underwriting, and risk assessment.
Governance is another dividing line. About 67.4% of AI leaders use centralised AI governance, compared with 23.5% of lagging insurers, and almost 85% have a dedicated chief AI officer, compared with 45.1% of lagging insurers. AI for Executives & Strategy resources address the governance and business alignment questions insurers face when scaling these systems.
"AI could upend the industry's long-standing structures and dynamics," McKinsey said.
Why this matters for insurance professionals
The insurers capturing AI's financial benefits share two traits: AI strategy tied directly to business goals, and centralised governance with executive ownership. For underwriters, claims staff, and distribution teams, the practical question is whether their company's AI projects are embedded in core systems or running as standalone experiments. The data suggests only the former produces measurable profit growth.
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