🔍 Read the full analysis: The AI Adoption Boom Hasn’t Meant Profits For Most Companies on ThorstenMeyerAI.com
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TL;DR
Company use of AI is expanding, but recent surveys show that measurable profit gains remain concentrated among a small share of firms. McKinsey found 6% of respondents met its definition of AI high performers, while BCG reported that 5% of surveyed companies were getting value at scale.
Companies are adopting AI more widely, but recent surveys suggest that relatively few report substantial profit gains from it. McKinsey’s 2026 survey found that 6% of respondents’ organisations qualified as AI “high performers,” while a separate BCG survey found 5% of 1,250 companies 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. That share was about the same as a year earlier. The survey’s high-performer category was narrower: organisations had to attribute at least 5% of EBIT to AI to qualify. These are survey responses, not audited financial results, and they do not establish that AI caused the reported outcomes.
BCG’s survey showed a similar divide. It found 5% of 1,250 firms had achieved value at scale, while 60% reported no material value. The figures come from different surveys with their own definitions and methods, so they should be read as evidence of a broad adoption-to-value gap, not as directly comparable measurements of all companies.
Adoption itself is increasing. Eurostat reported that 20.0% of EU enterprises with at least 10 employees used AI in 2025, up from 13.5%. Usage was reported by 55% of large enterprises and 17% of small enterprises. The European figures measure whether companies use AI; they do not show whether that use raised profits.
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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Adoption Has Not Guaranteed Returns
The gap matters because firms may spend on software, data preparation, staff training and risk controls without seeing measurable gains in profit. The surveys do not prove that AI investments have failed across the economy, but they do show that using AI is not the same as capturing value. For executives, the relevant test is whether a system improves a defined business outcome, not whether a company has launched a pilot.
The findings also bear on workers. McKinsey reported that 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 report, as described by The Register and TechTimes, also said last year’s actual cuts fell well short of respondents’ expectations. Those results reflect views reported in a survey; they do not establish how employment will change across the workforce.
For readers outside management, the distinction is practical: a company may use AI to speed up tasks without changing its headcount or improving its bottom line. The available figures do not identify which companies will benefit or how any gains will be distributed among businesses, workers and customers.
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From Digital Tools to Automated Work
The report frames the change as a move from digitising tasks to having software carry out parts of the work. Earlier business systems largely stored information and supported decisions made by people. Newer AI systems can, within defined limits, read documents, classify requests, retrieve information and take actions. The distinction is especially relevant to AI agents, which can perform sequences of steps rather than only produce a response to a prompt.
Survey results suggest agent use is growing, though the measures remain self-reported. BCG respondents said agents accounted for about 17% of their AI value and expected that share to reach 29% by 2028. McKinsey reported that 40% of companies with more than $1 billion in revenue said they were scaling agents, up from 27%. These figures describe respondents’ assessments and expectations, not independently verified returns.
The source argues that returns depend on redesigning workflows rather than adding a tool to an unchanged process. It also notes that workers may need to supervise AI actions, handle exceptions and remain accountable for outcomes. That shift creates operational and governance questions, including what an agent can access, which actions require approval and how its work is recorded.
“37 percent said AI has some effect on their company’s EBIT; only 6 percent qualify as “high performers” with at least 5 percent of EBIT attributed to AI.”
— McKinsey survey findings, as reported by The Register and TechTimes
Profit Measures Remain Uneven
The surveys use different definitions of AI adoption, financial impact and value at scale. Their results cannot be combined into one precise estimate of how many companies profit from AI. The McKinsey and BCG findings are survey responses, while Eurostat’s figures measure reported use in a defined population of EU businesses; none of the figures supplied establishes causation between AI and company earnings.
It is also unclear how many pilots will ultimately become routine operations, or whether expected gains from agents will appear in reported financial results. Gartner forecasts that more than 40% of agentic AI projects will be cancelled by the end of 2027 because of cost, unclear value or weak risk controls. It also forecasts that organisations will abandon 60% of AI projects lacking AI-ready data. These are projections, not confirmed future outcomes.
For European firms that considered AI but did not use it, the source reports that 71% cited missing expertise. The material does not specify the survey’s full methodology or give a comparable figure for every region, so the result should not be treated as a universal estimate of the skills gap.
Companies Face a Scaling Test
The next test is whether organisations can move from experiments to dependable use in core operations while tracking costs and results. BCG respondents said leading companies had deployed 62% of their AI initiatives, compared with 12% for lagging companies. That comparison is reported by BCG; it does not by itself explain why one group deployed more projects or prove that deployment produced financial returns.
Companies will also have to decide where people remain in control, what permissions automated systems receive and how errors are caught. The source argues that firms should focus on a small number of use cases, redesign whole workflows and measure outcomes. Gartner’s stated distinction is to use agents where decisions are needed, conventional automation for routine workflows and assistants for simple information retrieval.
Whether those approaches lift profits at scale remains unsettled. The reported forecasts extend through 2027 and 2028, while the survey figures describe current or recent respondent reports. Further evidence will depend on later surveys and company results that distinguish experimental use from sustained operational and financial effects.
Key Questions
Are most companies using AI?
Use is growing, but levels vary by company size and geography. Eurostat reported that 20.0% of EU enterprises with at least 10 employees used AI in 2025, including 55% of large firms and 17% of small firms. That measure does not establish how widely AI is used elsewhere.
In McKinsey’s 2026 survey, 6% of respondents’ organisations met its high-performer definition of attributing at least 5% of EBIT to AI. BCG separately reported that 5% of 1,250 surveyed companies were getting value at scale. The surveys use different methods and definitions.
Does AI use prove that a company is more profitable?
No. Adoption figures show that companies use AI, not that it caused higher profits. The reported survey findings indicate that some respondents see an effect, but they are not audited results or proof of causation.
Why do some AI projects fail to scale?
The source points to costs, unclear business value, weak risk controls and missing AI-ready data. Gartner forecasts cancellations for some agentic AI projects, but those projected cancellations have not all occurred.
What could AI adoption mean for workers?
McKinsey respondents who use AI often reported higher productivity, while a larger share expected job cuts than in the previous survey. Those are respondent views, not a confirmed forecast of employment outcomes; the source says previous cuts fell short of expectations.
Source: ThorstenMeyerAI.com
