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Surveys cited in a November 6, 2026 report show that AI use is spreading, while substantial profit gains remain uncommon. McKinsey found 6% of respondents attributed at least 5% of company EBIT to AI; BCG reported that 5% of surveyed companies achieved value at scale. Survey methods and populations differ, and the figures are self-reported.
In McKinsey’s survey of 1,719 respondents, 37% said AI had some effect on their company’s EBIT, roughly unchanged from a year earlier, according to coverage by The Register and TechTimes. The 6% figure refers to respondents who said AI accounted for at least 5% of EBIT and characterized its impact as significant. These are self-reported survey results; they do not establish that AI caused a particular company’s financial performance.
A separate BCG study of 1,250 companies found a similarly uneven picture: 5% said they were achieving value from AI at scale, while 60% reported no material value. BCG respondents said AI agents already generated about 17% of their AI value and expected that share to reach 29% by 2028. The report also says 35% of companies were scaling AI, but the measures and survey populations differ from McKinsey’s, so the percentages should not be treated as directly comparable.
Adoption figures vary by geography and company size. Eurostat reported that 20.0% of EU enterprises with at least 10 employees used AI in 2025, up from 13.5% in 2024. Use was reported by 55% of large enterprises and 17% of small ones. In McKinsey’s survey, 40% of respondents from companies with more than $1 billion in revenue said their firms were scaling AI agents, up from 27% a year earlier, according to The Register and TechTimes.
Most Companies Use AI, Few See Profits
Survey results show AI adoption spreading, while substantial financial returns remain uncommon. The figures reflect different self-reported surveys, not audited proof of AI’s impact.
Use is spreading
Eurostat tracks whether businesses use AI, not whether it improves their finances.
Adoption is not profit
The surveys measure different outcomes and populations, so their findings should not be combined into one rate.
- Companies report using AI across more operations.
- EU enterprise use rose from 13.5% in 2024 to 20.0% in 2025.
- Only a small share reported a major EBIT effect or value at scale.
- Survey answers are self-reported, not audited estimates.
What may hold projects back
Reported barriers point to the work needed to turn pilots into measurable results.
Skills are a constraint
71% of EU firms that considered AI but did not use it cited a lack of relevant expertise.
Scale remains difficult
The report points to workflow redesign, value tracking, selected use cases and clear limits on AI actions.
Some forecasts warn of cancellations
Gartner forecasts project cancellations tied to costs, unclear value, weak controls and data readiness.
Why AI Adoption Is Not Yet Paying Off
The survey gap matters because companies may be investing in AI without seeing a clear effect on earnings. Adoption rates alone do not show whether a system saves money, raises revenue or improves service enough to justify its costs. The reported financial figures also come from surveys, so they describe executives’ assessments rather than audited estimates of AI’s contribution.
The source report argues that the shift from digitizing tasks to letting software handle parts of a workflow changes what companies must manage. An AI system might read an invoice, compare it with a contract and flag exceptions. To produce value, that workflow needs reliable data, clear limits on the system’s actions and a way to measure results. BCG’s figures suggest that scaling remains uncommon: its survey found a gap between the 5% reporting value at scale and the 60% reporting no material value.
For workers, the findings combine reported productivity gains with concern about employment. The source report says 80% of McKinsey respondents who use AI reported higher productivity, while 39% expected job cuts, up from 32% a year earlier. Those expectations do not establish that cuts will occur. According to The Register and TechTimes, reductions in the prior year fell well short of what respondents had anticipated.
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Adoption Across Firms and Sectors
Earlier digital transformation projects often moved paper processes into software while leaving people responsible for reading cases and making decisions. The source report describes AI as a change in that division of work: systems can process unstructured material, such as emails, scanned invoices and support tickets, and take steps within limits set by a company.
That description is useful context for the current results, but it does not mean every company has deployed systems capable of handling an entire workflow. Eurostat’s adoption measure counts whether an enterprise used at least one AI technology; it does not measure financial returns. The McKinsey and BCG surveys ask different questions of different respondent groups, so their figures capture distinct aspects of adoption and perceived value.
Barriers remain. Eurostat data cited in the source report show that 71% of EU firms that considered AI but did not use it named a lack of relevant 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. Gartner also forecasts that organizations will abandon 60% of AI projects that lack AI-ready data. These are forecasts, not reported cancellation rates to date.
How Much Profit AI Actually Adds
The surveys do not establish a single, independently verified estimate of AI’s effect on corporate profits. The McKinsey results are based on respondents’ reports about their companies; the BCG study uses a different sample and definitions of value. The figures therefore cannot be combined into one adoption-to-profit rate.
It is also unclear from the cited material how respondents calculated AI’s contribution to EBIT, how they separated it from other business changes or whether outcomes differ by industry and use case. Gartner’s project-cancellation figures are forecasts, and the source material does not provide a later observed outcome. The reported productivity and job-cut expectations likewise do not establish long-term effects on output or employment.
Whether Pilots Reach Measurable Returns
The next signal will be whether companies can move AI projects beyond trials and report measurable results, including costs as well as benefits. The source report points to workflow redesign, a limited number of selected use cases, value tracking and rules governing what AI agents may do as practices used by stronger performers. BCG reported that leading companies had deployed 62% of their AI initiatives, compared with 12% among lagging companies; that comparison is from BCG’s study and does not by itself show which practices caused the difference.
Gartner’s forecast places attention on projects through the end of 2027, when it expects cancellations among agentic AI initiatives to rise for reasons including cost, unclear value and weak risk controls. Companies’ future disclosures and survey results may help show whether adoption is translating into financial outcomes, but the source material does not identify a specific upcoming measurement date or reporting milestone.
Key Questions
How many companies report a major profit effect from AI?
In McKinsey’s 2026 survey, 6% of respondents said AI accounted for at least 5% of their company’s EBIT and had a significant impact. This is a self-reported survey finding, not an independently audited estimate.
How widely is AI used by European businesses?
Eurostat reported that 20.0% of EU enterprises with at least 10 employees used AI in 2025, up from 13.5% in 2024. The reported rate was 55% among large enterprises and 17% among small ones. The measure tracks use, not financial value.
What did the BCG survey find about AI value?
BCG’s study of 1,250 companies found that 5% reported value at scale, while 60% said AI had produced no material value. These results use BCG’s definitions and survey population and should not be directly equated with McKinsey’s figures.
Why are some AI projects not delivering value?
The source report cites costs, unclear value, weak risk controls and a lack of AI-ready data as obstacles. It also says 71% of EU firms that considered AI but did not use it cited missing expertise, based on Eurostat data.
Will AI lead to job cuts?
The cited McKinsey survey found that 39% of respondents expected job cuts, up from 32% a year earlier. That records expectations, not confirmed job losses; the source report says cuts in the prior year fell short of what respondents had expected.
Source: Thorsten Meyer AI
