🔍 Read the full analysis: Most Companies Use AI. Why Do So Few Profit? on ThorstenMeyerAI.com
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TL;DR
AI use is spreading, but surveys cited by ThorstenMeyerAI.com show that only a small share of companies attribute substantial profit gains to it. The findings point to workflow redesign, data readiness and governance as persistent hurdles, while the scale of AI’s effects on jobs remains uncertain.
Most companies are using artificial intelligence, but only a small share report substantial profit gains from it, according to surveys reviewed in a November 6 report by ThorstenMeyerAI.com. McKinsey’s 2026 survey found that 6% of respondents’ organisations qualified as AI “high performers,” attributing at least 5% of earnings before interest and taxes to AI, while a separate BCG study found 5% of surveyed companies had achieved value at scale.
The figures point to a gap between adopting AI tools and changing business results. In McKinsey’s survey of 1,719 respondents, 37% said AI had some effect on their company’s EBIT, roughly the same share as a year earlier, according to coverage by The Register and TechTimes cited in the report. The 6% high-performer figure uses a narrower threshold: at least 5% of EBIT attributed to AI. It does not mean that the other respondents saw no benefit at all.
BCG’s study of 1,250 companies reported that 5% were getting value from AI at scale, while 60% said they had not achieved material value. The report also cites a difference in deployment: leading companies had deployed 62% of their AI initiatives, compared with 12% among laggards. These are survey findings, not a controlled comparison showing that deployment alone caused better financial performance.
Adoption rates vary by region and company size. Eurostat data cited in the report show that 20% 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. The report says European businesses that considered AI but did not use it most often cited a lack of expertise, 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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Why Adoption Has Not Become Profit
The findings matter because companies are moving beyond experiments while still struggling to show that AI improves their financial results. A tool can help an employee draft text or retrieve information without changing the overall cost, speed or quality of a business process. Larger gains may require redesigning how work moves across teams and systems, rather than adding a chatbot to an existing workflow.
The report describes AI agents as systems that can take steps such as reading an invoice, checking it against a contract, flagging an exception or drafting a response. That can shift employees from handling every routine step to supervising outputs and exceptions. It also increases the importance of clear permissions, review processes and accountability when software can act in connected systems.
For workers, the survey evidence presents both reported productivity benefits and concern about job losses. McKinsey respondents who used AI said it made them more productive in 80% of cases. At the same time, 39% expected their organisations to cut jobs, up from 32% in the previous survey, according to The Register and TechTimes. Expectations are not confirmed job losses; the report also says last year’s cuts fell short of what respondents had anticipated.
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From Digitised Tasks to Automated Work
The report frames the change as a shift from digitising a process to having software handle parts of the work. In earlier programmes, companies moved forms and records into digital systems, while people continued to interpret cases and make decisions. Newer AI systems can process less structured material, such as emails, scanned invoices and support tickets, and can take defined actions within limits set by an organisation.
That capability does not make every task suitable for an agent. The report attributes to Gartner a distinction between agents for work requiring decisions, conventional automation for routine workflows and assistants for simple information retrieval. Gartner also warns that connecting agents to older systems can be technically complex and disruptive. BCG’s survey similarly points to redesigning core workflows, rather than relying on isolated pilots, as a route to broader value.
Forecasts in the report underline the risks. Gartner predicts that more than 40% of agentic AI projects will be cancelled by the end of 2027 because of cost, unclear value or inadequate risk controls. It also forecasts that organisations will abandon 60% of AI projects that lack AI-ready data. These are forecasts, not completed cancellation rates.
What the Surveys Cannot Establish
The figures come from surveys and official statistics with different samples, definitions and time periods. “AI use,” “value at scale” and AI’s effect on EBIT are not interchangeable measures, so the reported percentages do not form a single adoption-to-profit conversion rate. The report summarizes McKinsey findings through coverage by The Register and TechTimes and does not provide enough detail here to assess every survey question or the financial calculations behind each response.
It is also unclear how much of the reported impact is directly attributable to AI rather than other business changes, or how results vary across industries and specific use cases. Gartner’s cancellation estimates remain forecasts. The job-loss figures describe respondents’ expectations, not a verified count of positions removed because of AI.
Whether Pilots Reach Production
The next test for companies is whether AI projects move from trials into routine operations with measurable results. The report points to workflow redesign, reliable data, focused use cases and controls over what agents can do as factors companies should address. Gartner’s forecast makes the coming period a test of whether organisations can resolve cost, value and risk concerns before projects are dropped.
Further evidence will be needed to show whether AI’s reported effects on EBIT grow beyond the current survey results, and whether productivity gains lead to changed staffing levels, different roles or both. The available figures do not settle those outcomes. They offer a snapshot of adoption and expectations, while the commercial and employment effects continue to develop.
Key Questions
How many companies report substantial profit gains from AI?
In the McKinsey survey cited by the report, 6% of respondents said their organisations met the definition of AI high performers: at least 5% of EBIT attributed to AI. BCG separately reported that 5% of the companies it surveyed were getting value at scale.
Does the report say most companies get no benefit from AI?
No. McKinsey found that 37% of respondents said AI had some effect on their company’s EBIT. The report distinguishes that broader measure from the smaller group meeting the high-performer threshold.
How common was AI use among EU businesses?
Eurostat figures cited in the report show that 20% of EU enterprises with at least 10 employees used AI in 2025, compared with 13.5% in 2024. The reported rate was 55% for large enterprises and 17% for small ones.
Why are some AI projects expected to be cancelled?
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. The figure is a forecast, not a reported cancellation rate to date.
What does the report say about AI and jobs?
McKinsey respondents reported productivity gains, while a growing share expected job cuts: 39%, up from 32% in the prior survey. Those figures describe user reports and expectations; they do not establish how many jobs AI has eliminated.
Source: ThorstenMeyerAI.com
