Artificial intelligence could finally break the insurance industry’s two-decade growth stalemate, according to a new McKinsey analysis. Gross written premiums have expanded roughly 4.9% annually since 2005, reaching an estimated $8.3 trillion in 2025, yet profits before tax grew only about 4.3% over the same period, reaching approximately $580 billion—a gap that forces and forces like globalization and digitization never managed to close.
McKinsey’s research shows that over the past five years, insurance sector AI leaders have created 6.1 times the total shareholder return (TSR) of AI laggards, a performance gap wider than in most other industries. This disparity underscores how dramatically AI adoption is reshaping competitive advantage in insurance.
The consulting firm argues that AI is fundamentally different from prior waves of technological change. Unlike digitization and platform economics, which tested insurance’s edges but left its underlying economic structure intact, AI addresses four dynamics that have defined the industry’s stagnation: fading relevance, high distribution costs, flat productivity, and a slow pace of change.
How AI Is Driving Measurable Gains
Best-in-class insurers adopting domain-based AI transformations—overhauling entire business functions rather than running isolated pilots—are already seeing concrete results. McKinsey found that domain-level implementations have delivered 10 to 20 percent improvements in new-agent success rates and sales conversion rates, 10 to 15 percent increases in premium growth, 20 to 40 percent reductions in costs to onboard new customers, and 3 to 5 percent accuracy improvements in claims.
One example McKinsey cited: UK insurer Aviva rolled out more than 80 AI models to improve outcomes in its claims domain, cutting liability assessment time for complex cases by 23 days, improving the accuracy of claims routing by 30 percent, and reducing customer complaints by 65 percent. Aviva reported that transforming its motor claims domain saved the company more than £60 million ($82 million) in 2024.
McKinsey also documented an insurance carrier that implemented intelligent automation for quote offerings and policy sales, moving 80 percent of transactions online and raising customer satisfaction scores—specifically, the likelihood customers would refer the insurer—by 36 percentage points. Another carrier deployed AI to generate roughly 50,000 claims-related communications daily, finding them clearer and more empathetic than those written by humans.
Reshaping Distribution, Risk Coverage, and Productivity
Distribution has remained largely unchanged despite decades of digitization: roughly 85% of U.S. property & casualty premiums and 95% of life insurance premiums flow through agents, brokers, and managing general agents. McKinsey found that 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 and recommend switches will redirect customers away from traditional agents. The firm expects disintermediation to move fastest in commoditized personal lines, while in complex segments like midmarket commercial and specialty risk, AI is more likely to compress costs and boost advisor productivity than replace them outright.
On the productivity front, insurance cost ratios are 17% higher globally than in 2005, even as sectors like telecommunications, automotive, and airlines reduced theirs. McKinsey found 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—but rather that those gains were offset by rising IT costs, compliance overhead, and the complexity of layering digital tools onto legacy systems. AI-driven transformations are already reversing this dynamic, producing the productivity and cost gains noted above.
McKinsey also identified the global protection gap as a key opportunity for AI-driven growth. Gross written premiums as a share of GDP have stayed flat across life, health, and property & casualty lines even as risk has intensified. 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, and less than 1% of global cyber costs are currently insured, a gap of roughly $900 billion.
McKinsey said AI could help the industry regain relevance by enabling new risk categories such as AI liability and nonphysical business interruption, shifting from reactive risk transfer to continuous risk monitoring through telematics-based coaching or AI-enabled health tracking, and improving underwriting and claims data to price previously uninsurable risks with more confidence.
Sources
- McKinsey & Company — Published July 15, 2025 report “The future of AI in the insurance industry,” detailing AI leaders’ 6.1x TSR advantage, domain-level transformation results, and Aviva case study.
- Risk & Insurance — July 23, 2026 article citing McKinsey analysis on two-decade growth stalemate, premium and profit growth figures, distribution structure, cost ratios, protection gap, and AI’s potential to reshape insurance economics.
