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TL;DR
Surveys cited in a November 6, 2026 report find that AI use is widespread but substantial financial returns remain concentrated among a small share of companies. The findings point to workflow redesign, usable data, clear measures of value and risk controls as key issues, while Gartner forecasts that many agentic AI projects could be cancelled.
A November 6 report on corporate AI adoption found a persistent gap between companies using AI and those reporting substantial profit gains: McKinsey’s 2026 survey put the share of respondents’ organisations with at least 5% of earnings before interest and taxes (EBIT) attributed to AI at 6%. The figures matter as companies consider moving from small AI pilots to systems that handle parts of business workflows.
The report compares several sources, which use different samples and definitions of AI use. In McKinsey’s survey of 1,719 respondents, 37% said AI had some effect on their company’s EBIT, roughly the same share as a year earlier. The report cites The Register and TechTimes as coverage of the survey. McKinsey’s “high performers” are defined as respondents attributing at least 5% of EBIT to AI; they made up 6% of the sample.
A separate BCG study of 1,250 companies found that 5% were getting value from AI at scale, while 60% reported no material value, according to the source report. These figures are not directly interchangeable with McKinsey’s: the surveys ask different questions and apply different measures. The report also cites Eurostat data showing that 20% of EU enterprises with at least 10 employees used AI in 2025, up from 13.5% in 2024. Adoption was reported by 55% of large enterprises and 17% of small enterprises.
The report argues that higher returns are associated with changing how work is done, rather than adding an AI tool to an unchanged process. It describes systems that can interpret inputs such as invoices or support tickets, consult other systems and take permitted actions, with people reviewing exceptions. BCG respondents said agents provided about 17% of their AI value and expected that share to reach 29% by 2028. McKinsey figures cited in the report indicate that 40% of companies with revenue above $1 billion said they were scaling agents, compared with 27% previously.
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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The Shift From Pilots to Workflows
The findings suggest that company leaders face a measurement and operating challenge, not simply a software-purchasing decision. If an AI system changes how invoices are checked, customer requests are handled or internal approvals are made, firms need to establish who is responsible for outcomes, what actions the system may take and how errors will be caught. Those choices affect cost, service quality and operational risk.
The possible effect on employees is mixed. The report says 80% of McKinsey respondents who use AI reported higher productivity. At the same time, 39% expected AI-related job cuts, up from 32% in the prior survey. Those are expectations, not confirmed employment losses; the report says earlier cuts fell short of what respondents had anticipated. The figures offer no definitive forecast of how jobs will change across industries.
For firms, the gap between adoption and returns makes it harder to judge success by the number of pilots or employees with access to a chatbot. The report points instead to measuring outcomes at the workflow level and limiting early projects to problems with a defined business case. That approach may also help companies decide when automation is appropriate and when a person should remain responsible for a decision.
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Adoption Varies by Company Size
The source report draws on official statistics, company surveys and forecasts, rather than one single study. Eurostat’s 2025 figures indicate that AI adoption across EU businesses is growing, but remains uneven by company size: 55% of large enterprises reported use, compared with 17% of small enterprises. Among European businesses that had considered AI but did not use it, the report says 71% cited missing expertise.
That adoption picture differs from the financial-return measures in McKinsey and BCG. Using AI somewhere in a business does not mean it has been integrated into a core process or generated a measurable effect on profit. The report describes the change as a move from digitising work—putting forms and records into software—to letting software perform parts of the work itself, while people supervise decisions and exceptions.
Forecasts add a note of caution. Gartner projects that more than 40% of agentic AI projects could 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. These are forward-looking estimates, not observed cancellation rates. The source report attributes them to Gartner forecasts and does not provide further details on the underlying forecast methodology.
Returns and Cancellations Remain Unsettled
The cited figures do not establish that AI caused a particular company’s profit change. McKinsey’s results are based on respondents’ reports, while BCG uses a separate study and measure of value. Survey responses, definitions and samples differ, so the percentages should not be combined into a single estimate of corporate AI performance.
Gartner’s cancellation figures are forecasts, and the report does not identify which industries or project types are most exposed. It also does not provide company-level examples or financial data to show why some implementations produce returns while others do not. The reported productivity and job expectations reflect survey respondents; they are not a direct count of realised productivity gains or job losses.
What Companies Will Measure Next
The next test for organisations will be whether deployed systems improve defined business outcomes, rather than whether a pilot can demonstrate a technical capability. The report recommends selecting a small number of use cases, tracking value and setting limits on what agents can do. It cites BCG survey results in which leading companies had deployed 62% of their AI initiatives, compared with 12% among lagging companies; the source does not give further detail here on how those groups were classified.
Companies are also likely to face practical decisions about data readiness, integration and oversight as they move projects into everyday operations. Gartner’s forecasts put those issues in focus, but do not settle how many current projects will be cancelled. Further survey results and reported financial outcomes will be needed to show whether wider adoption translates into sustained profit gains, and how productivity changes affect staffing.
Key Questions
In the McKinsey 2026 survey cited in the report, 6% of respondents qualified as high performers by attributing at least 5% of their company’s EBIT to AI. The figure is a survey result, not an audited count of companies.
Does the report show that AI use is increasing?
Yes, the cited Eurostat data show that 20% of EU enterprises with at least 10 employees used AI in 2025, up from 13.5% in 2024. Adoption was higher among large enterprises than small ones.
Why do some AI projects fail to reach production?
The report points to unclear value, costs, weak risk controls, missing expertise and data readiness as barriers. Gartner’s estimates about cancellations are forecasts, not confirmed outcomes.
What does the report say about AI and jobs?
It cites a survey in which 80% of respondents who use AI said it improved their productivity, while 39% expected job cuts. Those figures describe respondents’ reports and expectations; they do not establish how many jobs have been lost because of AI.
Source: ThorstenMeyerAI.com
