Artificial intelligence (AI) could generate $2.52 trillion in annual economic value globally by automating and supporting existing work, but rising deployment costs could significantly reduce these potential gains, according to an October 2026 report by McKinsey.
As per the titled The AI Value Curve: The Economics of Applying AI to Existing Work, the data highlights a growing gap between AI adoption and measurable economic returns. The study revealed that many organisations are focusing on implementing the technology rather than assessing the value it generates.
A 30% increase in effective AI costs could wipe out $850 billion in potential economic value annually, reducing AI's projected global impact from $2.52 trillion to $1.67 trillion, according to McKinsey estimates.
In the United States, the estimated annual economic value could fall from $960 billion to $640 billion under the same scenario. The report clarified that these figures represent a modelled scenario rather than a forecast.
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The findings come as companies increase spending on AI infrastructure, software and automation. McKinsey estimated that around $7 trillion could be invested in AI infrastructure by 2030, requiring approximately $760 billion in annual profit pools to justify the investment.
Financial Services Leads Potential Gains
Financial services emerged as the sector with the largest potential annual economic gains from AI, estimated at $530 billion. Education followed with $410 billion, while technology, media and telecommunications could generate $360 billion. Healthcare's potential economic value was estimated at $310 billion annually.
The report also highlighted the potential for AI to support highly skilled, higher-paid professionals rather than focusing exclusively on automating large volumes of lower-wage work. Legal services, healthcare, management and computer-related occupations were identified as areas offering significant opportunities for cost-effective AI deployment.
AI Economics Vary Across Countries
McKinsey emphasised that the economic benefits of AI differ across countries because of variations in labour costs. In labour-intensive economies, relatively lower wages can influence whether businesses benefit more from automating tasks or using AI to support human workers.
The analysis compares existing labour costs with the full cost of AI deployment, including technology expenses, human supervision, verification and rework. This suggests that technological capability alone does not determine whether an AI application makes economic sense.
Instead, businesses must assess whether the productivity gains justify the costs while maintaining acceptable work quality.
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