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TL;DR
Several surveys and forecasts cited in a November 6 report show a gap between business AI adoption and measurable financial returns. McKinsey found 6% of surveyed respondents’ companies attributed at least 5% of EBIT to AI, while BCG found 5% of surveyed firms were getting value at scale. The figures come from different studies and definitions; they point to scaling, workflow redesign and governance as ongoing challenges, not a single measure of AI’s overall impact.
Business use of AI is spreading faster than reported financial returns, according to a November 6 report comparing surveys from McKinsey, BCG and Eurostat. McKinsey’s 2026 survey found 6% of respondents’ companies met its definition of AI “high performers,” attributing at least 5% of earnings before interest and taxes (EBIT) to AI; BCG reported that 5% of 1,250 companies were getting value at scale.
The figures describe different surveys and measures, rather than a single, directly comparable count. In McKinsey’s survey of 1,719 respondents, 37% said AI had some effect on their company’s EBIT, a share reported as roughly unchanged from a year earlier. The report was covered by The Register and TechTimes. The 6% figure refers to the narrower “high performer” group, defined as companies attributing at least 5% of EBIT to AI.
BCG’s study of 1,250 firms found that 5% were getting value from AI at scale, while 60% reported no material value, according to the source report. BCG’s respondents said AI agents accounted for about 17% of AI value at the time of the study and expected that share to reach 29% by 2028. Those are survey findings and expectations, not audited financial results or a forecast that every company will achieve that level.
Adoption also varies by company size and location. Eurostat recorded AI use among 20.0% of EU enterprises with at least 10 employees in 2025, up from 13.5% in 2024. Use was reported by 55% of large enterprises and 17% of small enterprises. These adoption figures do not establish whether companies gained profit from using AI.
Infographic 01 · Who gets value from AI
Most companies use AI. About 6 percent profit from it in a big way
Adoption keeps rising. The share of companies that can show a large effect on profit has barely moved.
Share of McKinsey’s 2026 respondents who attribute at least 5 percent of their company’s EBIT to AI and call the impact significant. Flat versus 2025, as reported by The Register.
Wide use, thin profit
Different surveys, different bases: read each line with its source
Sources: McKinsey State of AI 2026 (n = 1,719), as reported by The Register, 25 Aug 2026 and TechTimes, 26 Aug 2026 · BCG, The Widening AI Value Gap, Sept 2025 (n = 1,250) · Eurostat, 11 Dec 2025 · Eurostat Statistics Explained (enterprises with 10+ employees). Survey figures are self-reported by executives; Eurostat counts use, not value.
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Why AI Adoption Has Not Meant Profit
The gap matters because companies are making decisions about technology spending, staffing and how work is organised. Adoption alone does not show that an AI project has reduced costs, increased revenue or improved margins. The survey results suggest that many firms are experimenting or using AI, while a much smaller share report substantial financial impact under the studies’ definitions.
The report points to a shift from installing software to redesigning work around it. AI agents can, within set limits, interpret information, consult other systems and take actions. That capability may change who handles routine steps, but it also creates responsibilities: companies need to define permissions, review exceptions and decide who is accountable for an outcome. The report’s evidence does not establish that agents will reliably deliver returns in every workflow.
For employees, the reported findings cut both ways. The source says 80% of McKinsey survey respondents who use AI reported productivity gains. It also says 39% expected job cuts, up from 32% in the previous survey; however, the report notes that job cuts in the prior period fell short of respondents’ earlier expectations. These are respondent views, not a count of jobs lost because of AI.
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Adoption, Returns and Agent Forecasts
The source report brings together evidence with different scopes: Eurostat’s official data on AI use among EU companies, BCG’s survey of 1,250 firms, McKinsey’s 2026 survey of 1,719 respondents and forecasts from Gartner. It also cites MIT’s “GenAI Divide” report through coverage by Fortune. Because the surveys ask different questions and use different definitions, their percentages should not be treated as measurements from one common sample.
Eurostat’s figures cover enterprises with at least 10 employees in the EU and measure whether they used AI, not whether they made money from it. The McKinsey figures concern respondents’ assessments of their companies’ AI impact and performance. BCG’s results refer to value at scale and material value. Keeping those distinctions clear is necessary to interpret the apparent gap between broad use and limited profit impact.
Gartner’s figures are forecasts, not observed outcomes. It predicts that more than 40% of agentic AI projects will be cancelled by the end of 2027 because of costs, unclear value or weak risk controls. Gartner also forecasts that organisations will abandon 60% of AI projects that lack AI-ready data. The report gives missing expertise as a common obstacle among European companies that considered AI but did not use it: 71% named it.
What the Survey Figures Cannot Show
The reported percentages do not provide a uniform, independently verified measure of AI’s effect on company profits. The studies use different populations, questions and definitions, and some findings are based on respondent assessments. The source material does not give enough detail to determine how much of each company’s reported financial impact can be attributed to AI rather than other changes.
It is also unclear how many projects will be cancelled under Gartner’s forecast, or how agent deployment will affect jobs across sectors. The 2028 agent-value share is an expectation reported by BCG respondents, not a confirmed future result. The figures should not be read as proof that AI generally fails to pay off, or that the small high-performing group’s outcomes will be replicated by other companies.
Projects Face a Scaling Test
The next evidence to watch is whether companies can move beyond pilots and show measurable financial results from AI in defined workflows. The source report says BCG respondents in the leading group had deployed 62% of their AI initiatives, compared with 12% among lagging firms. Those figures describe deployment rates in the survey, not a guarantee that deployment produces returns.
Gartner’s forecast puts project cancellations through the end of 2027 on the watch list, particularly where costs, business value, risk controls or data readiness remain unresolved. Companies will also face decisions about which actions AI agents may take without human approval and how their work will be monitored.
Further survey results and company-level disclosures may clarify whether the adoption-to-profit gap narrows. For now, the available findings show extensive experimentation and use alongside limited reported high-level returns; they do not settle which business models or workflows will produce the most durable gains.
Key Questions
How many companies are reporting major financial gains from AI?
In McKinsey’s 2026 survey, 6% of respondents’ companies met its “high performer” definition: attributing at least 5% of EBIT to AI. BCG separately reported that 5% of surveyed firms were getting value at scale. The measures differ and are not directly interchangeable.
How widespread is AI use among European businesses?
Eurostat reported that 20.0% of EU enterprises with at least 10 employees used AI in 2025, up from 13.5% in 2024. The rate was 55% for large enterprises and 17% for small enterprises. These figures measure use, not profitability.
Why are companies struggling to get value from AI?
The source report points to challenges including costs, unclear business value, weak risk controls, data readiness and a lack of expertise. Gartner’s forecasts also warn that integrating agents into existing systems can disrupt workflows.
Are AI agents already contributing to business value?
BCG respondents said agents accounted for about 17% of AI value at the time of its study and expected the share to reach 29% by 2028. The latter is a survey-based expectation, not a verified future outcome.
Do the findings show that AI is cutting jobs?
No. The source reports that 39% of McKinsey respondents expected job cuts, up from 32%, but also says earlier cuts fell short of respondents’ expectations. Those figures describe views about staffing, not confirmed job losses caused by AI.
Source: ThorstenMeyerAI.com
