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TL;DR
AI use is spreading across companies, but survey results show that substantial profit gains remain concentrated among a small minority. McKinsey’s 2026 survey found 6% of respondents’ organizations met its high-performer threshold, while BCG reported that 5% of surveyed companies had achieved value at scale.
AI adoption is widespread, but only about 6% of companies in a 2026 McKinsey survey qualified as high performers by attributing at least 5% of earnings before interest and taxes (EBIT) to AI, according to figures reported by The Register and TechTimes. The result highlights a gap between businesses trying AI and those reporting substantial financial returns.
McKinsey’s survey included 1,719 respondents. Thirty-seven percent said AI had some effect on their company’s EBIT, a share that was about the same as a year earlier. The 6% high-performer figure uses a more demanding measure: respondents’ organizations had to attribute at least 5% of EBIT to AI. These are survey findings, not independently audited company accounts, and the results reflect respondents’ assessments.
Boston Consulting Group found a similar divide in a survey of 1,250 companies: 5% said they were achieving value from AI at scale, while 60% reported no material value. BCG also found a difference in deployment between leaders and laggards: leading organizations had deployed 62% of their AI initiatives, compared with 12% among lagging organizations. Those figures describe groups defined in BCG’s research; they do not establish that deployment alone caused the difference in value.
Adoption figures vary by population and definition. Eurostat reported that 20.0% of EU enterprises with at least 10 employees used AI in 2025, up from 13.5% in 2024. Usage stood at 55% among large enterprises and 17% among small enterprises. The European figures measure reported use, not whether AI increased profits, so they cannot be directly compared with the McKinsey or BCG financial-value measures.
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 Use Is Not Yet Profit
The gap matters because companies may spend on software, computing, integration, staff training and risk controls without seeing a clear return in their financial results. The survey findings suggest that buying or testing AI is not the same as capturing value. For executives, the challenge is to identify where AI improves an operating result and to measure that result against a credible baseline, rather than treating the number of pilots or users as proof of success.
BCG and the source article point toward redesigning end-to-end workflows rather than attaching AI to one isolated task. An AI system might read an invoice, compare it with a contract and flag an exception; people would still set permissions, review uncertain cases and take responsibility for outcomes. That can change how work is organized, but the available survey figures do not show that every such redesign will save money or raise profits.
For employees, the implications are mixed. The source article reports that 80% of McKinsey respondents who use AI said it made them more productive. At the same time, 39% expected job cuts, up from 32% a year earlier. Those are reported views, not a count of jobs actually eliminated. The article also says last year’s cuts fell short of respondents’ expectations, underscoring the difference between forecasts about employment and observed outcomes.
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Adoption Measures Differ by Survey
The report draws on several sources that measure different things: official use statistics, company surveys and forecasts. Eurostat measures whether enterprises report using AI. McKinsey asks respondents about AI’s effect on company EBIT and defines a high performer using a threshold. BCG reports whether firms say they have reached value at scale. Each provides a different view, and none should be read as a universal estimate of AI’s financial effect across all companies.
The source article describes a shift from digitizing a process—moving records and forms into software while people make decisions—to letting software handle more steps. AI agents are systems that can take actions across a workflow, rather than only retrieve information or generate a response. McKinsey reporting cited in the article says that, among companies with more than $1 billion in revenue, 40% reported scaling agents, up from 27%. The survey’s specific definition of “scaling” and the underlying comparison period are not detailed in the supplied material.
Forecasts point to implementation risks, but they are not observed outcomes. Gartner predicts that more than 40% of agentic AI projects could be cancelled by the end of 2027 because of cost, unclear value or weak risk controls. Gartner also forecasts that organizations will abandon 60% of AI projects that lack AI-ready data. The source says European companies that considered AI but did not use it most often cited missing expertise, at 71%; it does not give the full survey details or denominator for that figure.
“Only 6% qualify as “high performers” with at least 5% of EBIT attributed to AI.”
— McKinsey survey findings, as reported by The Register and TechTimes
How Much Value Is Verified?
The figures are based on surveys and reported company assessments, so they do not establish audited, causal profit gains. The source material does not provide full questionnaires, sampling methods or confidence intervals for each result. It also does not specify precisely how respondents calculated AI’s contribution to EBIT or how BCG defined value at scale.
The survey populations and measures differ, making direct comparisons limited. The figures do not establish whether a company’s AI use caused a change in profits, whether gains persisted over time, or how costs of implementation were counted. Gartner’s cancellation estimates are forecasts, not a record of projects already abandoned. The supplied material also gives no detailed breakdown of which industries, use cases or company sizes account for the reported high performers.
Employment effects remain uncertain too. Reported productivity improvements and expectations of job cuts do not show how many roles have been removed, created or changed because of AI. The source material provides no verified job-loss total tied to these surveys.
Tracking Results Through 2027
Companies will need to show whether AI produces measurable results beyond adoption counts, including how gains compare with implementation and oversight costs. For agent projects, that means defining what actions systems may take, who reviews exceptions and how performance is evaluated. These are practical measures raised by the source article, not a guarantee that a project will succeed.
The next notable forecast in the material is Gartner’s prediction that more than 40% of agentic AI projects will be cancelled by the end of 2027. That outcome remains to be seen. Further company surveys and financial disclosures may clarify whether the small share reporting significant value grows, and whether reported productivity gains translate into sustained profit changes. The source material does not identify a specific upcoming survey release or reporting date.
Key Questions
What does the 6% figure mean?
It refers to the share of respondents’ organizations classified as high performers in McKinsey’s 2026 survey, based on attributing at least 5% of EBIT to AI. It is a survey result, not an audited count of companies.
Does the survey say that only 6% of companies use AI?
No. The 6% figure concerns a high threshold for reported financial impact. In the same McKinsey survey, 37% of respondents said AI had some effect on their company’s EBIT. Separately, Eurostat found 20.0% of EU enterprises with at least 10 employees used AI in 2025.
What did BCG find?
In its survey of 1,250 companies, BCG reported that 5% achieved value at scale and 60% reported no material value. These results use BCG’s survey measures and should not be treated as identical to McKinsey’s EBIT threshold.
Are AI agents already affecting jobs?
The source material reports that more McKinsey respondents expected job cuts—39%, up from 32%—but does not provide a verified total of jobs lost because of AI. Expectations and reported productivity gains are not the same as measured employment effects.
What could happen to AI projects by 2027?
Gartner forecasts that more than 40% of agentic AI projects could be cancelled by the end of 2027 because of cost, unclear value or weak risk controls. This is a forecast, not a confirmed cancellation rate.
Source: ThorstenMeyerAI.com
