A recent analysis by management consultancy firm McKinsey & Company predicts that AI will play a key role in shaping the future of the insurance industry. Insurers, distributors and technology providers that begin adopting AI early will be better positioned to adapt to industry changes and benefit from the shift towards a technology-first future.
Noting that the sector has historically been resistant to major disruption, McKinsey stated that while developments like globalisation, digitalisation and platform-based business models have reshaped many industries, they have had a more limited impact on insurance’s underlying economic structure.
“While the global insurance industry has experienced steady premium growth over the past two decades, improvements in operating leverage have been limited across property and casualty (P&C), life and health insurance, and a management consulting firm,” McKinsey noted.
As per the management consultancy firm, gross written premiums have increased by around 4.9% annually since 2005. The tally reached approximately USD 8.3 trillion in 2025, while profits before tax have grown by around 4.3% during the same period, reaching approximately USD 580 billion. Rising capital requirements have contributed to this slower profit growth.
“Competitive positions have shifted gradually, capital movement across regions and business lines has remained relatively slow, and public markets have generally continued to view insurance as a stable industry with predictable earnings,” McKinsey said.
While the private capital has introduced innovation in areas such as balance sheet management and investment strategies, it has had less impact across other parts of the insurance value chain. As per McKinsey, the insurance industry of 2026 would remain recognisable to executives who viewed the sector in 2006.
“This stability has also brought benefits. The insurance industry has continued to provide significant shareholder returns through dividends and share buybacks, while maintaining an important role in supporting economies and societies, including during major events such as the global pandemic,” McKinsey stated further.
Talking about AI’s role in transforming the insurance industry, McKinsey sees the sector facing increasing pressure from the disruptive tech, with the latter having the potential to influence four long-standing industry challenges: slower growth and declining relevance, high distribution costs, limited productivity gains and a historically gradual pace of change.
“There is a growing gap between rising global risks and the insurance industry’s ability to provide coverage. Insurance revenues have grown more slowly than many major industries and global GDP, with personal lines representing 1% of global GDP in 2023 compared with 1.2% in 2019. Growth in developed markets has often been driven by pricing increases rather than expansion into new areas of risk,” McKinsey noted.
The firm also highlighted significant protection gaps in emerging risk areas. As per its estimates, the global natural catastrophe protection gap reached USD 133 billion in 2025, while less than 1% of global cyber costs are currently insured, representing a potential gap of around USD 900 billion. The company argues that insurance is becoming less aligned with an increasingly complex risk environment.
Keeping the above-mentioned industry challenges in mind, McKinsey pitched for the AI’s aggressive adoption within the industry ecosystem, as the move could create opportunities for the sector through new risks, new solutions and expanded market access. AI may also introduce additional areas of insurable risk, including AI liability, non-physical business interruption and workforce-related risks linked to AI adoption.
As per the consultancy giant, next-generation elements like parametric insurance, embedded micro-coverage and real-time data-driven policies could make insurance accessible to customers and risks that have previously been difficult to serve economically.
While highlighting a potential shift from traditional risk transfer towards broader risk partnerships, McKinsey explains that conventional insurance has largely focused on responding after losses occur, whereas AI could give the sector the real edge by enabling insurers to provide continuous monitoring, insights and prevention support before incidents happen.
“Examples of this approach could include telematics systems that provide real-time driving guidance while adjusting premiums, commercial risk management supported by satellite and Internet of Things data, and AI-enabled health support designed to improve health outcomes. These approaches already exist in limited areas but have not yet become central to the wider insurance proposition,” McKinsey noted.
“AI could further improve access to insurance markets by strengthening underwriting and claims capabilities. Emerging risks like climate-related property risks, cyber threats and AI-related exposures remain difficult to price because insurers lack sufficient reliable data and predictive confidence,” it added further.
As per McKinsey, improved data analysis, continuous model updates and more accurate claims assessment could help insurers price risk more effectively and expand coverage. Carriers developing these capabilities early may gain advantages through improved loss ratios, stronger pricing confidence and the ability to enter markets where competitors may remain cautious.
However, challenges remain too, with the consultancy firm noting that some digital risks not behaving like traditional insurance exposures, as shared infrastructure, interconnected supply chains and common technology dependencies could create 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.