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TL;DR
Surveys cited in a November 6, 2026, report show a gap between companies using AI and those reporting substantial financial returns. McKinsey found 6% of respondents’ organisations attributed at least 5% of EBIT to AI, while BCG reported that 5% of surveyed firms had achieved value at scale. The findings point to workflow redesign, data readiness, expertise and governance as factors in whether pilots produce measurable results.
Most companies are using AI in some capacity, but only a small share report substantial financial returns, according to a review of surveys and forecasts published by ThorstenMeyerAI.com on November 6. McKinsey’s 2026 survey found that 6% of respondents said AI contributed at least 5% of their organisation’s earnings before interest and taxes (EBIT), while BCG reported that 5% of surveyed companies had generated value from AI at scale.
The findings point to a gap between adoption and business impact. In McKinsey’s survey of 1,719 respondents, 37% said AI had some effect on their company’s EBIT, a share reported as roughly unchanged from the previous year. The results were reported by The Register and TechTimes. The 6% figure refers to organisations meeting McKinsey’s definition of “high performers”: at least 5% of EBIT attributed to AI. It is a survey result, not an independently verified measure of company earnings.
BCG’s survey of 1,250 firms found that 5% were getting value from AI at scale, while 60% reported no material value. The report says the firms making greater progress were changing core workflows rather than relying on isolated experiments. BCG respondents reported that leaders had deployed 62% of their AI initiatives, compared with 12% among lagging companies. These are survey findings, and they do not by themselves establish why one group performed better.
Adoption also varies by company size and location. Eurostat reported that 20.0% of EU enterprises with at least 10 employees used AI in 2025, up from 13.5% in 2024. The rate was 55% among large enterprises and 17% among small ones. Those figures measure reported use, not the financial return from that use, and should not be read as a direct comparison with the McKinsey or BCG results.
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 Pilots Often Fail to Scale
The difference between using AI and earning a return from it matters to companies deciding where to spend on software, staff and data infrastructure. The source report argues that AI can change the work itself: systems may read incoming documents, check them against other records, flag exceptions and draft responses. That shifts the challenge from installing a tool to deciding which steps can be automated, where people must review decisions and how results will be measured.
Survey results suggest that this shift is not yet routine. In BCG’s findings, most companies had not achieved material value at scale. Gartner forecasts that more than 40% of agentic AI projects will be cancelled by the end of 2027 because of costs, unclear value or inadequate risk controls. Gartner also forecasts that organisations will abandon 60% of AI projects that lack AI-ready data. These are forecasts, not confirmed cancellation rates.
The implications extend to employees, though the available figures describe expectations and reported experience rather than confirmed job outcomes. McKinsey respondents who used AI largely said it improved their productivity, while a growing share expected job cuts. Companies still need to determine whether productivity gains will lead to changed roles, reduced hiring, lower costs or increased output.
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From Digitised Forms to AI Workflows
Earlier digital transformation efforts often moved paper processes onto screens while leaving people responsible for interpreting each case and taking action. The report describes AI as a possible change to that arrangement: software can handle parts of the work, with a person stepping in for exceptions or oversight. AI agents, in particular, can take multiple steps within permissions set by an organisation, rather than only generating an answer to a prompt.
The source draws on several kinds of evidence that measure different things. Eurostat provides official statistics on AI use by European businesses; McKinsey and BCG report survey responses; Gartner provides forecasts; and the MIT “GenAI Divide” report is discussed through coverage by Fortune. Their samples, definitions and questions are not interchangeable. The headline figures therefore show a broad pattern, but do not form a single, directly comparable measure of corporate AI performance.
One cited barrier in Europe is a shortage of expertise: among firms that considered AI but did not use it, 71% named missing expertise, according to Eurostat figures in the source report. That finding points to implementation capacity as one hurdle alongside data quality, costs and risk management. The report also says BCG respondents expect agents’ share of AI value to rise from about 17% to 29% by 2028; that is a respondent expectation, not a measured future outcome.
What the Surveys Cannot Yet Show
The surveys do not establish that AI caused the reported financial results. They rely on respondents’ descriptions of their organisations, and the source report does not provide enough methodological detail to reconcile the studies’ definitions of AI use, value or scale. The 6% and 5% figures come from different surveys and should not be combined or treated as a common industry-wide measurement.
It is also unclear how much of the reported productivity improvement translates into sustained profit, and whether the gains are concentrated in particular industries or tasks. Gartner’s cancellation projections and respondents’ expectations about future agent value are not observed outcomes. The source material gives no company-by-company accounting that would show which deployments produced returns after costs.
For workers, McKinsey respondents’ expectations of job cuts are not evidence that those cuts have occurred because of AI. The source says 39% expected job reductions, up from 32%, and notes that cuts in the prior year fell short of what respondents had anticipated. The survey does not settle how future adoption will affect employment, wages or job duties.
Companies Face a Scaling Test
The next test for businesses is whether they can move from pilots to carefully measured use in core workflows. The source report says leading firms are selecting a limited set of applications, tracking outcomes and redesigning processes, while setting boundaries for what agents can do. For deployments that can send messages, approve transactions or alter records, permissions, review procedures and audit logs are part of the implementation question, not an afterthought.
Gartner’s forecast that more than 40% of agentic AI projects will be cancelled by the end of 2027 provides a future benchmark, but it remains a projection. Companies and readers will need later evidence on project cancellations, costs and realised returns to judge whether adoption is producing lasting financial results. Until then, the surveys support a narrower conclusion: AI use is growing, but widespread, measurable profit impact has not yet been shown.
Key Questions
How many companies report substantial financial returns from AI?
In McKinsey’s 2026 survey, 6% of respondents said their organisations attributed at least 5% of EBIT to AI. BCG separately reported that 5% of 1,250 surveyed firms had achieved value at scale. The studies use different definitions and should not be treated as directly comparable.
Does AI use mean a company is making money from it?
No. Eurostat’s 2025 figure that 20.0% of EU enterprises with at least 10 employees used AI measures adoption, not profit. The surveys cited in the report show that reported use is more common than substantial financial returns.
Why are companies struggling to scale AI?
The source report points to workflow changes, implementation costs, unclear value, weak risk controls, data readiness and a lack of expertise. Eurostat figures cited in the report say 71% of European firms that considered but did not use AI named missing expertise.
Are AI agents replacing workers?
The material does not establish that AI agents have caused a particular level of job losses. McKinsey survey respondents reported productivity benefits and greater expectations of job cuts, but expectations are not confirmed employment outcomes.
What is expected to happen to agentic AI projects?
Gartner forecasts that more than 40% of agentic AI projects will be cancelled by the end of 2027, citing costs, unclear value or weak risk controls. That is a forecast; the eventual cancellation rate remains unknown.
Source: ThorstenMeyerAI.com
