🔍 Read the full analysis: Can More Companies Profit From AI? The Adoption Gap Explained on ThorstenMeyerAI.com
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TL;DR
AI use is growing, but surveys cited in a November 6 report find that substantial financial returns remain concentrated in a small minority of companies. McKinsey’s 2026 survey says 6% of respondents’ organizations attribute at least 5% of EBIT to AI, while BCG found 5% of surveyed firms were getting value at scale. The gap points to workflow redesign, data readiness, skills and risk controls as key challenges.
AI adoption is spreading across companies, but only a small share report substantial financial returns, according to surveys compiled in a November 6 report by ThorstenMeyerAI.com. McKinsey’s 2026 survey found that 6% of respondents’ organizations attributed at least 5% of earnings before interest and taxes (EBIT) to AI, while a BCG survey found 5% of 1,250 companies were getting value from AI at scale.
The figures describe different surveys and measures, not a single direct comparison. In McKinsey’s survey of 1,719 respondents, 37% said AI had some effect on their organization’s EBIT, a share reported as roughly unchanged from the previous year. The report cites The Register and TechTimes for those findings. The 6% classified as “high performers” said AI accounted for at least 5% of EBIT.
BCG’s survey of 1,250 companies found that 5% were generating value at scale, while 60% reported no material value, according to the source article. BCG respondents also estimated that AI agents—systems that can take steps toward a task rather than only generate answers—already produced about 17% of their AI value and forecast a 29% share by 2028. These are survey responses and expectations, not independently verified measures of future returns.
AI use is also advancing unevenly by company size and region. Eurostat data cited in the report show that 20.0% of EU enterprises with at least 10 employees used AI in 2025, up from 13.5% in 2024. The reported share was 55% among large enterprises and 17% among small ones. For firms that considered AI but did not use it, missing expertise was the most commonly reported obstacle, at 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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Profit Depends on Changing Workflows
The findings suggest that buying or testing AI tools is not the same as changing business performance. The source report says BCG respondents associated greater value with reshaping core workflows end to end, rather than relying on isolated pilots. That means organizations may need to change how work moves between people and software, not simply add an AI feature to an existing system.
That shift can affect operating costs, service speed and how employees spend their time. McKinsey respondents who used AI reported productivity gains: 80% said it made them more productive. At the same time, 39% expected job cuts linked to AI, up from 32% in the prior survey, according to the source’s account of McKinsey findings. Expectations are not evidence that those cuts have occurred; the report says earlier anticipated reductions exceeded the cuts reported later.
For business leaders, the gap matters because AI investment can carry costs in software, integration, data preparation and oversight before benefits appear. For employees, it signals that AI may change tasks and supervision even when a company has not shown a clear financial return. The available survey figures do not establish that AI alone caused reported productivity or employment changes.
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From Digitized Tasks to AI Agents
The report frames the development as a change from putting existing processes into software to having software handle parts of the work itself. Traditional systems typically stored information or moved it between steps while a person interpreted a case and chose what to do. AI systems can work with less-structured material, such as emails or invoices, and may classify it, retrieve related records or draft a response.
AI agents add the possibility of taking actions within rules set by an organization. The source attributes to Gartner a distinction between agents for decisions, automation for routine workflows and assistants for simple information retrieval. It also reports that, among companies with more than $1 billion in revenue, 40% said they were scaling agents, compared with 27% previously, citing McKinsey findings reported by The Register and TechTimes.
Those capabilities bring practical demands. Agents that can contact customers or trigger transactions need defined permissions, records of their actions and human review for exceptions. The source says BCG respondents from leading companies had deployed 62% of their AI initiatives, compared with 12% among lagging companies. The figures describe deployment rates reported in that survey; they do not, by themselves, show which management practices caused the difference.
““Most large companies now use AI somewhere. Only a small minority can show that it moves their profit.””
— Thorsten Meyer, source article author
How Much Return AI Delivers
The surveys do not provide one common definition of AI use, “value at scale” or financial impact, so their percentages should not be treated as interchangeable. The source does not give full survey questionnaires, response rates or detailed methods for every finding it summarizes. The reported results also rely on respondents’ assessments, rather than a single audited measure of AI’s causal effect on company profits.
Gartner’s forecasts cited in the article warn 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. These are forecasts, not cancellation outcomes already observed. It remains unclear which sectors or types of projects will be most affected, and how quickly companies can address shortages in expertise, data and governance.
Track Projects Through 2027
The next useful test is whether companies can show that AI projects move beyond pilots into sustained use with measurable outcomes. The Gartner forecast puts attention on project cancellations through the end of 2027, while BCG respondents expect agents’ share of AI value to increase by 2028. Those dates are forecasts and expectations, not confirmed milestones.
Companies will need to disclose clearer measures of costs, productivity and financial impact for comparisons to become more meaningful. Further survey releases may show whether the reported gap narrows, but they cannot alone establish that AI caused changes in profits or jobs. Until then, the current evidence points to broadening adoption alongside limited reported returns at scale.
Key Questions
How many companies report substantial financial returns from AI?
In McKinsey’s 2026 survey, 6% of respondents’ organizations qualified as high performers by attributing at least 5% of EBIT to AI. BCG separately found that 5% of its 1,250 surveyed companies were getting value at scale. The measures differ and should not be combined.
Is AI adoption increasing in Europe?
Yes. Eurostat data cited in the report show that 20.0% of EU enterprises with at least 10 employees used AI in 2025, up from 13.5% in 2024. Adoption was higher among large firms than small firms in the reported figures.
Why do some AI projects fail to produce value?
The report points to disconnected pilots, workflows that have not been redesigned, missing expertise, unprepared data, costs and weak risk controls. Gartner’s cited figures are forecasts about project abandonment, not a count of failures already confirmed.
Are AI agents replacing employees?
The source describes agents as systems that can take steps toward tasks under defined limits, often with people supervising exceptions. Some McKinsey respondents expected more job cuts, but those expectations do not establish that cuts occurred or that AI caused them.
Source: ThorstenMeyerAI.com
