🔍 Read the full analysis: AI At Work: Why Only A Small Share Of Companies Profit on ThorstenMeyerAI.com
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TL;DR
Surveys cited in a November 6 report show a gap between companies using AI and those reporting meaningful profit gains. McKinsey found 6% of respondents’ companies met its definition of high performers, while BCG found 5% of surveyed firms had achieved value at scale. The findings point to workflow redesign, data readiness and governance as barriers, though the surveys do not establish that AI alone caused companies’ financial results.
A small share of companies report substantial financial gains from artificial intelligence even as adoption spreads, according to surveys and forecasts reviewed in a November 6 report by ThorstenMeyerAI.com. McKinsey’s 2026 survey found 6% of respondents’ companies met its definition of AI “high performers,” while BCG reported that 5% of 1,250 firms were getting value from AI at scale.
In McKinsey’s survey of 1,719 respondents, 37% said AI had some effect on their company’s earnings before interest and taxes, or EBIT. The report said that share was about the same as a year earlier. The 6% designated high performers attributed at least 5% of EBIT to AI, according to coverage of the survey by The Register and TechTimes. These are survey responses, not independently audited estimates of AI’s causal effect on profit.
BCG’s study of 1,250 companies found a similar concentration: 5% reported that they had achieved value at scale, while 60% said they had not gained material value. The source article says BCG also found that leading companies had deployed 62% of their AI initiatives, compared with 12% among lagging firms. The figures suggest that launching projects and turning them into operating changes are different stages, though the studies use their own definitions and should not be treated as directly comparable.
Adoption remains uneven by company size and geography. Eurostat reported that 20.0% of EU enterprises with at least 10 employees used AI in 2025, up from 13.5%. The share was 55% among large enterprises and 17% among small ones. Among European firms that had considered AI but did not use it, 71% cited a lack of expertise, according to the figures in the source report.
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 Rarely Reaches the Bottom Line
The gap matters because companies are moving from buying software that supports workers to testing systems that can carry out steps in a task. AI tools may classify incoming cases, retrieve information, draft responses or act within set limits. If such systems change how work is done, the investment can affect costs, service times and staffing—not just the software budget.
But adoption alone does not show that those outcomes have improved. A company may have a pilot or an AI feature in use without changing the wider process or showing a measurable financial return. BCG’s findings, as presented in the source report, point to end-to-end workflow redesign rather than isolated experiments as a path to larger gains. That is a reported interpretation of the survey, not proof that redesign guarantees profit.
The change also affects employees and managers. McKinsey respondents who used AI reported productivity improvements: 80% said AI made them more productive. At the same time, 39% expected job cuts, up from 32% in the prior year’s survey. The source notes that job cuts in the previous period fell short of what respondents had expected. Expectations are not confirmed employment outcomes, and the survey does not establish how jobs will change across industries.
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From Digitized Screens to AI Workflows
Earlier digital-transformation programs often moved paper-based tasks into software while leaving people to interpret information and make decisions. The newer AI pitch is that systems can process some of that work: read an email or invoice, check related records, identify exceptions and take an approved action. The source article describes this as a shift from digitizing a process to letting software process parts of the work.
AI agents are systems designed to take multiple steps toward a task, rather than only answer a prompt. Their wider use is still developing. BCG respondents said agents already generated about 17% of their AI value and expected the share to reach 29% by 2028. McKinsey’s survey, as reported by The Register and TechTimes, found that among companies with more than $1 billion in revenue, 40% said they were scaling agents, up from 27%. These are survey findings and expectations, not independent measures of agents’ financial contribution.
Forecasts also underline the implementation risks. Gartner forecast 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. It also forecast that organizations would abandon 60% of AI projects lacking AI-ready data. Those are predictions, not completed cancellations or observed outcomes.
What the Survey Figures Cannot Prove
The available figures do not settle how much AI itself caused companies’ reported financial results. The surveys rely on respondents’ accounts, and the source material does not provide enough detail to compare their definitions of AI use, value at scale or high performance directly. A company’s reported EBIT effect is not necessarily an independently verified causal estimate.
It is also unclear how many projects will reach sustained use after pilots, how the forecasts for cancellations will compare with actual outcomes, or how AI adoption will affect employment over time. The report identifies data, expertise, cost and governance as barriers, but does not provide a single estimate of how much each factor explains the gap in returns. The employee figures describe reported productivity and job-cut expectations, not a definitive forecast of future jobs.
The Test Is Sustained Business Value
The next test for companies is whether AI projects move beyond trials into routine operations and produce results that organizations can measure. The source report points to choosing a limited number of uses, redesigning workflows, tracking financial outcomes and setting rules for what agents can do. Those are proposed approaches, not guarantees of success.
Gartner’s forecast puts project cancellations through the end of 2027 on the watch list, while BCG’s survey records an expectation that agents will contribute a larger share of AI value by 2028. Future reporting and updated company surveys will show whether those expectations are met. For now, the evidence supports a narrower conclusion: AI use is growing, but reported profit gains remain concentrated, and the reasons include both implementation challenges and the difficulty of measuring returns.
Key Questions
How many companies report substantial AI profit gains?
In McKinsey’s 2026 survey, 6% of respondents’ companies qualified as high performers by attributing at least 5% of EBIT to AI. BCG reported that 5% of 1,250 firms achieved value at scale. The surveys use different measures.
Does the research prove AI caused higher profits?
No. The figures are survey findings based on respondents’ reports. They do not by themselves establish that AI caused a company’s financial results or provide an independently audited return on investment.
How common is AI use among European companies?
Eurostat reported that 20.0% of EU enterprises with at least 10 employees used AI in 2025, up from 13.5%. Usage was 55% among large enterprises and 17% among small ones.
Why do some AI projects fail to deliver value?
The source report cites unclear value, costs, weak risk controls, data limitations and a lack of expertise. Gartner forecast that more than 40% of agentic AI projects could be cancelled by the end of 2027, but that remains a forecast.
What does the report say about AI and jobs?
McKinsey respondents who used AI often reported productivity gains, while 39% expected job cuts, compared with 32% in the prior year’s survey. Those figures measure reported experience and expectations, not confirmed future employment changes.
Source: ThorstenMeyerAI.com
