AI Could Break Insurance’s Two-Decade Growth Stalemate, McKinsey Says
Global insurers have grown premiums steadily but seen little improvement in profitability or efficiency over the past 20 years, according to McKinsey & Company.
Gross written premiums expanded roughly 4.9% annually since 2005, reaching an estimated $8.3 trillion in 2025, while profits before tax grew only about 4.3% over the same period, reaching approximately $580 billion, McKinsey found. The firm said forces that transformed other industries, including globalization, digitization and platform economics, tested insurance’s edges but never altered its underlying economic structure.
Artificial intelligence, McKinsey argues, is different: It could reshape four dynamics that have defined the industry’s stagnation, including fading relevance, high distribution costs, flat productivity and a slow pace of change.
A Widening Protection Gap
Gross written premiums as a share of GDP have stayed flat across life, health and property & casualty lines even as risk has intensified, McKinsey found. Personal lines represented 1% of global GDP in 2023, down from 1.2% in 2019.
The global protection gap for natural catastrophes reached $133 billion in 2025, according to Aon data cited in the analysis, and less than 1% of global cyber costs are currently insured, a gap of roughly $900 billion, according to the Financial Stability Institute.
McKinsey said AI could help the insurance industry regain relevance through three paths:
- New risk categories such as AI liability and nonphysical business interruption.
- A shift from reactive risk transfer to continuous risk monitoring, such as telematics-based coaching or AI-enabled health tracking.
- And improved underwriting and claims data that would let carriers price previously uninsurable risks with more confidence.
But the firm cautioned that digital risks, including AI liability and systemic cyber exposure, may be highly correlated and difficult to diversify, warning that carriers entering these lines without new analytical capability risk “chasing premium in a growing category before the underlying risk structure is understood.”
Distribution’s Grip May Loosen
Roughly 85% of U.S. property & casualty premiums and 95% of life insurance premiums are distributed through agents, brokers and managing general agents, McKinsey found, a structure largely unchanged by prior waves of digitization. Distributors have consistently outperformed carriers in total shareholder returns, aided by commissions that have barely moved since 2005, though McKinsey noted markets registered one of the largest share declines in decades this year amid recognition of AI’s threat to distributors.
McKinsey said nearly half of North American customers already use AI in their personal insurance-buying journeys, raising questions about whether agentic AI tools that monitor renewals, compare coverage and recommend switches will redirect the “front door” to customers away from agents and carrier websites. The firm said disintermediation is likely to move fastest in commoditized personal lines, while in more complex segments such as midmarket commercial and specialty risk, AI is more likely to compress costs and boost broker productivity than replace advisers outright.
Productivity Gains Erased by Rising Costs
Insurance cost ratios are 17% higher globally than in 2005, even as sectors such as telecommunications, automotive and airlines reduced theirs, McKinsey found. The firm said this was not a failure of technology to improve labor productivity, which rose 14% in property & casualty and 24% in life insurance across claims, servicing and policy issuance. Instead, those gains were offset by rising IT costs, compliance overhead and the complexity of layering digital tools onto legacy systems.
McKinsey said AI-driven transformations are already producing 20% to 40% reductions in customer onboarding costs and 10% to 20% improvements in agent productivity, and the firm identified two viable competitive paths going forward:
- Scale, in which large carriers amortize AI infrastructure costs across bigger premium bases
- Deep specialization, in which firms excel narrowly and access other capabilities through partners.
McKinsey also found that AI leaders in the industry have generated six times greater total shareholder returns than laggards.
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