McKinsey’s October 2026 report estimates AI could generate USD 2.52 trillion in annual global economic value from existing work, ANI reported on 24 October. The firm models a drop to USD 1.67 trillion if effective AI costs rise 30%, a reduction of around 34%, or USD 850 billion.
The report, titled The AI value curve: The economics of applying AI to existing work, covers both automation and support for workers. McKinsey’s calculation includes technology costs, human supervision, verification and rework. It describes the estimates as a modelled scenario rather than a forecast.
In the United States, McKinsey estimates the same cost increase could shrink annual value by USD 320 billion, from USD 960 billion to USD 640 billion. It puts financial services at USD 530 billion in potential annual gains, followed by education at USD 410 billion.
McKinsey puts possible spending on AI infrastructure at around USD 7 trillion by 2030 and calculates approximately USD 760 billion in yearly profit pools would be needed to make those outlays worthwhile. It recommends that businesses assess changing AI costs and plan to redeploy employees as work changes.
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