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TL;DR
McKinsey’s 2026 survey found that 37% of respondents said AI had some effect on their company’s EBIT, while 6% met its definition of high performers, attributing at least 5% of EBIT to AI. Separate BCG research also found a sharp gap between broad experimentation and results at scale; survey findings and forecasts point to workflow redesign, data, skills and risk controls as factors shaping whether projects deliver value.
Only 6% of companies in McKinsey’s 2026 survey qualified as AI “high performers,” meaning respondents attributed at least 5% of company EBIT to AI, according to reports by The Register and TechTimes. The finding highlights a gap between adoption and measurable financial returns: 37% of respondents said AI had some effect on EBIT, while many companies remain unable to show substantial gains.
The McKinsey survey included 1,719 respondents. Its reported figure of 37% who saw some effect on EBIT was about the same as a year earlier. The 6% high-performer figure uses a narrower threshold: those respondents said AI accounted for at least 5% of their company’s earnings before interest and taxes. The figures are survey responses, not an audited measure of AI’s contribution across all companies.
Boston Consulting Group’s separate study of 1,250 companies found a comparable concentration of reported value. BCG said 5% of firms were getting value from AI at scale, while 60% reported no material value. The two surveys use their own definitions and samples, so their percentages should not be treated as directly interchangeable. Both indicate that reporting AI use is more common than reporting substantial business results.
Adoption is still expanding. Eurostat reported that 20.0% of EU enterprises with at least 10 employees used AI in 2025, up from 13.5% in 2024. The 2025 rate was 55% among large enterprises and 17% among small ones. Those official EU figures measure use, not whether AI increased profits. Among EU firms that considered AI but did not use it, the most frequently cited obstacle was a lack of relevant expertise, reported by 71%.
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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From AI Adoption to Profit
The gap matters because companies are moving beyond experiments toward systems that can act across business processes. A chatbot that drafts a response is different from an AI agent that reads a request, checks records, makes a decision within set limits and takes an action. The latter may affect more of a workflow—and raises questions about permissions, oversight and responsibility alongside potential savings or added revenue.
For company leaders, the survey results caution against using the number of pilots or tools purchased as a proxy for business impact. BCG’s research suggests that results at scale are associated with changing core workflows rather than adding isolated AI features. In its survey, companies classified as leaders had deployed 62% of their AI initiatives, compared with 12% among laggards. That is a reported difference in deployment, not proof that deployment alone caused stronger financial outcomes.
For employees, reported productivity benefits coexist with concern about staffing. McKinsey found that 80% of respondents who use AI said it made them more productive. At the same time, 39% expected job cuts, up from 32% in the prior survey, according to The Register and TechTimes. The source also reports that cuts in the previous year fell short of what respondents had expected. The survey captures expectations and reported experience; it does not establish how many jobs AI will ultimately replace.
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Use Is Not the Same as Impact
The figures come from different kinds of evidence. Eurostat provides official statistics on AI use among EU businesses. McKinsey and BCG report surveys of respondents about adoption, business impact and organisational practices. Gartner’s numbers are forecasts, not counts of completed project cancellations. Differences in definitions, samples and questions mean these findings provide several views of the trend rather than one unified estimate of AI’s financial return.
One change under discussion is the move from digitising a process to having software handle steps within it. In traditional systems, software might store a case while a person reads it, decides what to do and clicks through the process. AI systems can work with less structured material, such as emails or invoices, and may classify it, retrieve related information or draft an action for a person to review. Agents can take steps on their own within defined permissions, making workflow design and oversight part of the implementation.
BCG respondents said agents accounted for about 17% of their AI value and expected that share to reach 29% by 2028. McKinsey’s survey, as reported by The Register and TechTimes, found that among companies with more than $1 billion in revenue, 40% said they were scaling agents, compared with 27% previously. These are survey findings and expectations, not guarantees that agent use will produce returns.
“Only 6% qualify as “high performers” with at least 5% of EBIT attributed to AI.”
— McKinsey 2026 survey findings, as reported by The Register and TechTimes
How Much Value AI Adds
The surveys do not establish that AI alone caused the reported changes in company earnings, and the available summary does not provide audited financial results for the firms counted as high performers. It is also unclear how much the results vary by industry, country or the particular AI applications companies use. Survey responses reflect what participants report and how each study defines impact.
Gartner forecasts 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. It also forecasts that organisations will abandon 60% of AI projects that lack AI-ready data. These are predictions, not observed cancellation rates. The source material does not specify the full project definitions, sample or method behind each forecast, so the figures should be read as Gartner’s outlook rather than a settled outcome.
It remains unclear how quickly companies will move from reported productivity gains to sustained profit changes, and whether expectations about job cuts will match later employment data. The findings do not identify a single cause for the gap between AI use and financial returns; expertise, data quality, project costs and workflow design are among the issues raised in the cited material.
The Test Is Scaling Safely
The next test for businesses is whether they can move selected AI projects into regular operations and measure their results against a clear baseline. That means tracking costs as well as benefits, identifying which stages of a workflow the system handles, and deciding when a person must review an output or exception. The cited surveys do not set a single timetable for that shift, but BCG’s respondents expect agents’ share of AI value to rise by 2028.
Companies adopting agents will also need to set limits on what systems can do, keep records of actions and assign responsibility for errors or exceptions. Gartner’s forecast on cancellations makes project costs, unclear business value and risk controls central issues to watch through 2027. Whether those warnings translate into the predicted level of cancellations remains to be seen.
Future survey results and company disclosures may show whether AI’s wider adoption is producing more measurable earnings impact. For now, the figures distinguish three different questions: whether companies use AI, whether they report productivity or operational benefits, and whether they can attribute a meaningful share of profit to it. The latest surveys suggest the last measure remains uncommon.
Key Questions
What does the 6% figure mean?
In McKinsey’s 2026 survey, 6% of respondents’ companies met the “high performer” definition: they attributed at least 5% of EBIT to AI. It is a survey finding, not an audited measure of all companies.
How many EU businesses used AI in 2025?
Eurostat reported that 20.0% of EU enterprises with 10 or more employees used AI in 2025, compared with 13.5% in 2024. Use rates were 55% for large enterprises and 17% for small ones.
Do the surveys prove AI increases company profits?
No. They report what participating respondents said about AI’s effect on their organisations. The findings do not establish that AI caused the reported earnings impact, and the studies use different samples and definitions.
Why do many AI projects fail to reach scale?
The cited material identifies several potential barriers, including unclear value, cost, weak risk controls, data readiness and lack of expertise. Gartner’s project-cancellation figures are forecasts, while Eurostat’s skills figure describes a reported obstacle among EU firms that considered but did not use AI.
Source: ThorstenMeyerAI.com
