Global insurance premiums reached an estimated $8.3 trillion in 2025, but the industry has lagged behind others in cost efficiency. AI could reduce customer onboarding costs by 20% to 40% and boost agent productivity by 10% to 20%, according to a McKinsey & Company report.
Operating expenses as a share of revenue rose 10% globally between 2005 and 2025, and 22% in North America. Pre-tax profits grew more slowly than premiums, climbing about 4.3% a year to roughly $580 billion.
Where AI can cut costs
AI tools can improve underwriting, claims handling and pricing. This opens the door to covering risks that are currently difficult to price, such as cyber threats, climate-related losses and AI liability. Less than 1% of global cyber costs are insured, leaving a protection gap of about $900 billion. The gap for natural catastrophes hit $133 billion in 2025.
Agent productivity improvements of 10% to 20% are possible with wider technology adoption. Insurers exploring AI for Insurance are advised to invest in data and technology and rethink their operating models.
Distribution shifts
About 85% of US property and casualty premiums and 95% of life insurance premiums are currently distributed through agents, brokers and managing general agents. AI assistants may increasingly compare policies, monitor renewals and recommend providers, particularly for simpler products.
Risks and strategy
McKinsey warned that AI-related and cyber risks may be highly connected, making losses harder to diversify and price. Insurers that treat AI as a gradual technology upgrade risk falling behind competitors that embed it across their entire business.
Why this matters for insurance professionals
The cost-saving potential is immediate, but the strategic stakes are higher. Firms must decide whether to compete on scale or specialist expertise. Those who move quickly to integrate AI into underwriting, claims and distribution can capture efficiency gains while competitors are still piloting programs.
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