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TL;DR
AI use is spreading across companies, but survey findings suggest that substantial profit gains remain concentrated among a small minority. The figures come from different surveys and definitions, while forecasts point to cost, data and governance problems as reasons projects may stall.
Companies are adopting AI faster than they are turning it into measurable profit, according to a November 6 report by ThorstenMeyerAI.com comparing European adoption data, corporate surveys and industry forecasts. In McKinsey’s 2026 survey, 37% of respondents said AI had some effect on their company’s EBIT, while 6% met the survey’s definition of high performers, attributing at least 5% of EBIT to AI.
The gap also appears in a Boston Consulting Group survey of 1,250 companies: 5% said they were generating value from AI at scale, while 60% reported no material value. These are survey results, not audited measurements of company-wide returns, and the two studies use their own definitions of value and performance.
Adoption is more advanced at larger organizations. Eurostat reported that 20% of EU enterprises with at least 10 employees used AI in 2025, up from 13.5% in 2024. The 2025 figure was 55% among large enterprises and 17% among small ones. Those official statistics measure use, not whether the technology increased profits.
The report also points to growing interest in AI agents, which can carry out steps in a task rather than only respond to prompts. BCG respondents estimated agents account for about 17% of their AI value today and projected that share would reach 29% by 2028. McKinsey survey findings, reported by The Register and TechTimes, said that among companies with more than $1 billion in revenue, 40% said they were scaling agents, compared with 27% in an earlier survey. These figures reflect respondent reports and expectations, not independently verified future outcomes.
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 Pilots to Measurable Returns
The findings suggest that the business challenge is no longer just acquiring AI tools; it is deciding where they can improve work and measuring whether they do. The source report says BCG respondents associated greater value with redesigning core workflows, rather than relying on isolated pilots. BCG’s survey also found that leaders had deployed 62% of their AI initiatives, compared with 12% among laggards.
That shift can affect how companies organize projects and how employees interact with software. The report describes a move from people handling each step on a screen toward systems processing routine material and escalating exceptions for human review. That is a description of the potential direction of work, not evidence that companies have broadly replaced human decision-makers.
There are also implications for workers’ expectations. In McKinsey’s survey, 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. The source notes that cuts reported in the previous period fell short of what respondents had expected. The survey does not establish how many jobs AI will eliminate, or how outcomes will differ across industries.
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Adoption Depends on the Measure
The figures should not be treated as one unified scorecard. Eurostat measures whether businesses use AI; McKinsey asks respondents about effects on earnings and organizational practices; BCG examines perceived value and deployment. Differences in samples, questions and definitions mean the results offer separate views of adoption and returns, rather than directly comparable estimates.
The report frames AI as a change to the work a system performs, not simply another software installation. Older digitization projects often moved forms and records into digital systems while leaving people to interpret and act on them. AI tools can process unstructured inputs such as invoices, emails and support tickets, and may take actions within set limits. Whether that works reliably depends on the task, the data and the controls in place.
Barriers remain common. Eurostat data cited in the report show that among European firms that considered AI but did not use it, 71% named a lack of relevant expertise. Gartner forecasts that organizations will abandon 60% of AI projects that lack AI-ready data. These are a reported obstacle and a forecast, respectively—not a finding that 60% of current projects have already failed.
“Over 40% of agentic AI projects will be cancelled by the end of 2027 because of cost, unclear value or weak risk controls.”
— Gartner forecast, as reported by ThorstenMeyerAI.com
Returns and Project Outcomes Remain Unclear
The surveys do not establish that AI caused the reported changes in EBIT or productivity. They rely on respondents’ assessments, and the reported percentages use different definitions. The source material does not provide enough detail to calculate a single comparable return-on-investment figure across the studies.
It is also unclear how many companies have deployed agents in live operations at scale, how often they require human correction, or what costs are included in reported value. Gartner’s projected cancellation rates remain forecasts, and the actual outcomes will depend on project choices and conditions. The source does not identify which industries or job categories will see the largest employment effects.
Watch Deployment Through 2027
Companies and investors will be watching whether reported pilots become sustained use in core operations, and whether firms can link those deployments to measured financial results. Gartner’s forecast places potential cancellations of more than 40% of agentic AI projects by the end of 2027, while BCG respondents expect agents’ share of AI value to rise by 2028. Both figures should be treated as forward-looking estimates.
For firms, the near-term tests are likely to include data readiness, the cost of operating systems, clear limits on what agents can do, and defined human responsibility for exceptions. Further survey releases and company disclosures may clarify whether adoption is narrowing the gap with profit gains. For now, the evidence supports a distinction between using AI and demonstrating that it has improved financial performance.
Key Questions
How many companies report substantial profit gains from AI?
In McKinsey’s 2026 survey, 6% of respondents’ organizations qualified as high performers, defined as attributing at least 5% of EBIT to AI. BCG separately found that 5% of surveyed companies generated value from AI at scale. The studies use different samples and definitions.
How common is AI use among European companies?
Eurostat reported that 20% of EU enterprises with at least 10 employees used AI in 2025, compared with 13.5% in 2024. Use was reported by 55% of large enterprises and 17% of small enterprises.
What is an AI agent?
In the source report, an AI agent is a system that can take steps toward completing a task, such as classifying information or looking up records, within limits set by an organization. The report distinguishes agents from tools that only retrieve information or automate routine workflows.
Why do some AI projects fail to scale?
The source cites cost, unclear business value, weak risk controls, data that is not ready for AI and limited expertise as barriers. Gartner’s cancellation estimates are forecasts, not evidence that all such projects have already been abandoned.
Do the surveys show that AI is eliminating jobs?
No. McKinsey respondents reported higher expectations of job cuts, but the survey does not establish how many jobs AI will eliminate. The source also says previously reported cuts fell short of respondents’ earlier expectations.
Source: ThorstenMeyerAI.com
