🔍 Read the full analysis: Most Companies Use AI. Only About 6 Percent Profit From It on ThorstenMeyerAI.com
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TL;DR
A McKinsey survey of 1,719 respondents found that 37% said AI had some effect on their company’s EBIT, while 6% met the survey’s definition of a high performer: attributing at least 5% of EBIT to AI. Other surveys also show a gap between adoption and material value, while forecasts point to cost, data and governance as common obstacles.
Most companies are using AI, but a small share report substantial profit gains: in McKinsey’s 2026 survey, 6% of respondents’ companies qualified as high performers by attributing at least 5% of earnings before interest and taxes, or EBIT, to AI. The survey of 1,719 respondents also found that 37% said AI had some effect on EBIT, a finding that underscores the gap between adoption and measurable financial returns.
The figures were highlighted in a November 6 report by ThorstenMeyerAI.com, which reviewed McKinsey, BCG, Eurostat and Gartner material. The McKinsey results were reported by The Register and TechTimes. The 6% figure is not a count of all companies worldwide: it reflects the survey’s definition of a high performer and the responses gathered from its participants. The source report says the share reporting some EBIT effect was about the same as a year earlier.
BCG’s survey of 1,250 firms points to a similar concentration of results. According to the report, 5% of the surveyed companies were getting value from AI at scale, while 60% reported no material value. BCG respondents said AI agents accounted for about 17% of their AI value and expected that share to reach 29% by 2028. These are survey findings and expectations, not independently verified measures of future performance.
Adoption varies by company size and geography. Eurostat data cited in the report show that 20.0% of EU enterprises with at least 10 employees used AI in 2025, up from 13.5% in 2024. The reported 2025 rate was 55% among large enterprises and 17% among small ones. In McKinsey’s survey, 40% of companies with more than $1 billion in revenue said they were scaling AI agents, up from 27%, according to The Register and TechTimes.
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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Adoption Is Outpacing Measured Returns
The gap matters because companies may be investing in AI without yet seeing a material effect on earnings. Adoption figures alone do not show whether a tool saves money, raises revenue or changes productivity. The McKinsey and BCG results suggest that reported financial value is concentrated among a small portion of survey participants, even as experimentation and deployment spread.
The source report describes the shift as moving from digitising existing processes to letting software handle parts of the work. AI systems can process unstructured material, such as invoices or support requests, and take bounded actions across business systems. If that changes how work moves through an organisation, companies may need to redesign entire workflows rather than add a tool to an unchanged process. That is an interpretation of the findings, not a measured conclusion from the surveys alone.
For employees, the impact is also unsettled. The report says 80% of McKinsey respondents who use AI reported that it made them more productive. At the same time, 39% expected job cuts, up from 32% in the prior survey, while earlier reported cuts fell short of respondents’ expectations. These responses describe perceptions and expectations; they do not establish how many jobs AI has eliminated.
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From Digital Tools to AI Agents
Traditional business digitisation often moved paper processes onto screens while leaving people responsible for reading cases, making decisions and taking action. The report argues that AI agents can shift some of that work to software: interpreting incoming information, consulting other systems and acting within assigned limits. An agent is more than a tool that answers a question; it can take multiple steps toward a task.
The source report attributes to Gartner guidance that agents are suited to cases requiring decisions, while conventional automation fits routine workflows and assistants suit simple information retrieval. It also cites Gartner warnings that adding agents to legacy systems can be technically difficult and disrupt workflows. BCG’s survey similarly associates greater value with reshaping core workflows rather than relying on isolated pilots.
The data also point to barriers beyond technology. The report says 71% of European firms that had considered AI but did not use it cited a lack of expertise. Gartner forecasts 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. It also forecasts that organisations will abandon 60% of AI projects that lack AI-ready data. These are forecasts, not counts of cancellations that have already occurred.
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How Much Profit AI Adds Remains Unclear
The figures come from surveys with different participants, methods and definitions, so they are not directly interchangeable. “Using AI,” “having an effect on EBIT,” and “getting value at scale” describe different things. The reported 6% figure means respondents’ companies met McKinsey’s high-performer threshold; it does not establish that exactly 6% of all companies worldwide earn significant profits from AI.
The material provided does not give the full survey wording, response rates or a breakdown of how companies calculated the share of EBIT attributable to AI. It also does not establish that AI alone caused the reported financial effects. The cited forecasts about project cancellations and data readiness are predictions, and the source material does not provide later outcomes against which to test them.
Companies Face a Test of Scale
The next test will be whether firms can turn pilots into sustained results while controlling costs, data quality and the authority given to automated systems. The report says BCG’s leading companies had deployed 62% of their AI initiatives, compared with 12% among lagging companies, though it does not provide enough detail here to determine how those groups were defined or how deployment translated into profit.
Gartner’s cited cancellation forecast sets the end of 2027 as a horizon for judging how many agentic projects are dropped. In the meantime, companies will need to disclose what they count as AI value and how they measure it. The available survey results establish a gap between adoption and reported returns; whether that gap narrows as systems are integrated into core workflows remains an open question.
Key Questions
What does the 6% figure mean?
It is the share of companies represented by respondents in McKinsey’s 2026 survey that met its high-performer definition: at least 5% of EBIT attributed to AI. It is not a verified global count of all companies.
Does the survey say most companies make no money from AI?
No. The survey says 37% of respondents reported some effect on EBIT, while 6% met the higher high-performer threshold. Those categories do not show that every other company made no return; the source material does not provide a full breakdown of financial outcomes.
How common was AI use in the European Union?
Eurostat data cited in the report say 20.0% of EU enterprises with at least 10 employees used AI in 2025, compared with 13.5% in 2024. The rate was 55% for large enterprises and 17% for small ones.
Why do AI projects fail to deliver value?
The report cites costs, unclear business value, weak risk controls, poor data readiness and a lack of expertise as barriers. Gartner’s cancellation figures are forecasts, while the 71% expertise figure refers to European firms that considered AI but did not use it.
Will AI lead to widespread job cuts?
The cited survey records expectations, not a confirmed forecast of job losses. It says 39% of respondents expected cuts, up from 32%, while earlier reported cuts were below what respondents had expected. The material does not establish how many jobs AI has eliminated.
Source: ThorstenMeyerAI.com
