What happened
McKinsey's flagship annual Global Survey on AI, based on responses from 1,719 professionals and business leaders worldwide, finds that individual productivity gains are outpacing enterprise financial returns: 80% of respondents say AI has improved their individual productivity, while only 37% attribute at least some EBIT impact to AI use — 'about the same share as last year' — and just 6% qualify as 'AI high performers' (organizations attributing ≥5% of EBIT to AI with 'significant' impact), a figure that has remained flat year-over-year. Agentic AI scaling is accelerating unevenly: 40% of respondents at organizations with over $1 billion in annual revenue report scaling AI agents, up from 27% last year, and nearly a third (32%) say their organization has decided against buying software in favor of building it in-house with agentic coding tools. Roughly 20% of respondents say AI-related operating costs are constraining their AI use, and workforce-reduction expectations are rising (39% expect declines vs. 32% last year), even though actual 2025 job cuts fell well short of prior-year predictions. The survey methodology and full findings are published as a 30+ page report on McKinsey's QuantumBlack insights site.
Why it matters
This is the industry's most widely cited AI-adoption benchmark; boards and CFOs use it to calibrate whether their own AI investment-to-return ratio is ahead of or behind the market, and the flat EBIT-impact/high-performer figures directly challenge the ROI narratives embedded in many FY27 AI budget requests.
Action needed
Benchmark internal AI EBIT-impact and agentic-scaling metrics against the survey's high-performer criteria (≥5% EBIT impact, workflow redesign) before finalizing next fiscal year's AI investment case.