In a recent analysis, management consulting firm McKinsey & Company examined how artificial intelligence (AI) will affect the future direction of the global insurance industry, arguing that as the industry structure evolves, insurers, distributors and technology providers that prepare early may be better positioned.
McKinsey & Company says the global insurance industry has experienced steady premium growth over the past two decades, but limited improvements in operating leverage across property and casualty (P&C), life and health insurance.
The company estimates that total premiums have grown about 4.9% annually since 2005 to reach about $8.3 trillion in 2025, while pretax profits have grown about 4.3% over the same period to about $580 billion. McKinsey noted that rising capital requirements have led to slower profit growth.
The company said the insurance industry has historically been able to withstand major disruptions. McKinsey said that while developments such as globalization, digitization and platform-based business models have reshaped many industries, their impact on the underlying economic structure of the insurance industry has been more limited.
Competitive positions are gradually shifting, capital flows across regions and business lines remain relatively slow, and public markets generally continue to view insurance as a stable industry with predictable returns.
McKinsey & Company noted that private capital has introduced innovations in areas such as balance sheet management and investment strategies, but has had less of an impact on other parts of the insurance value chain. The company said the insurance industry in 2026 will still be recognizable to executives who followed the industry in 2006.
The company acknowledges that this stability also brings benefits. The insurance industry continues to provide strong returns to shareholders through dividends and share buybacks, while maintaining an important role in supporting the economy and society, including during major events such as the global pandemic.
However, McKinsey believes the industry is now facing increasing pressure from AI, which has the potential to impact four long-standing industry challenges: slower growth and relevance, high distribution costs, limited productivity improvements, and the historically incremental pace of change.
McKinsey found a growing gap between rising global risks and the insurance industry’s ability to provide coverage. Insurance revenue is growing slower than many major industries and global GDP, with personal insurance revenue growing at 1% of global GDP in 2023, compared with 1.2% in 2019, the company said. Growth in developed markets tends to be driven by pricing increases rather than expansion into new risk areas, the company said.
The company highlighted significant protection gaps in emerging risk areas. McKinsey estimates that the global natural disaster protection gap will reach $133 billion by 2025, noting that less than 1% of global network costs are currently insured, implying a potential gap of approximately $900 billion. The company believes it is increasingly difficult for insurance to adapt to an increasingly complex risk environment.
McKinsey & Company believes that AI can create opportunities for the industry through new risks, new solutions and expanded market access. The company noted that AI may introduce other areas of insurable risk, including AI liability, non-physical business interruption and workforce-related risks associated with AI adoption.
It also shows that technologies such as parametric insurance, embedded microinsurance and real-time data-driven policies can enable customers to obtain insurance and take on risks that were previously difficult to afford economically.
The company also highlighted a potential shift from traditional risk transfer to broader risk partnerships. McKinsey explains that while traditional insurance focuses primarily on response after a loss occurs, AI can enable insurers to provide continuous monitoring, insight and prevention support before an incident occurs.
Examples of this approach include telematics systems that provide real-time driving guidance while adjusting premiums, commercial risk management powered by satellite and IoT data, and AI-powered health supports designed to improve health outcomes, McKinsey said. The company said these approaches already exist in limited areas but have not yet become central to the broader insurance proposition.
McKinsey further believes that AI can improve access to insurance markets by enhancing underwriting and claims capabilities. The company noted that some emerging risks, including climate-related property risks, cyber threats and artificial intelligence-related risks, remain difficult to price because insurers lack sufficient reliable data and forecast confidence.
Improved data analytics, ongoing model updates and more accurate claims assessment can help insurers price risk more effectively and expand coverage, the company said. Operators that can develop these capabilities early may gain an advantage through improved loss ratios, increased pricing confidence and the ability to enter markets where rivals may be wary, McKinsey said.
However, McKinsey also highlighted potential challenges. The company noted that certain digital risks may behave differently than traditional insurance risks, as shared infrastructure, connected supply chains and common technology dependencies can result in highly correlated losses. Insurers entering these areas will need strong analytical capabilities to understand how risks develop and spread, rather than simply creating new products, McKinsey said.
The company concluded that artificial intelligence could create opportunities and challenges for insurance institutions. McKinsey says success depends not only on adopting AI models, but also on leveraging the technology to create unique capabilities and long-term competitive advantage.
