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TL;DR
Companies are adopting AI, but surveys cited by ThorstenMeyerAI.com show that only a small share report substantial profit effects. The figures point to a gap between experimentation and operational value: companies must redesign workflows, measure results and manage risk, while the scale of future gains remains uncertain.
Most companies using AI have not shown substantial profit gains, according to surveys and forecasts reviewed in a November 6 analysis by ThorstenMeyerAI.com. The article cites McKinsey research in which 6 percent of respondents’ companies qualified as “high performers,” attributing at least 5 percent of earnings before interest and taxes (EBIT) to AI, while a Boston Consulting Group survey found just 5 percent of 1,250 companies were getting value at scale.
The figures do not mean that AI has no effect at other companies, though many still struggle to close the gap between using AI and making a profit from it. In McKinsey’s 2026 survey of 1,719 respondents, 37 percent said AI had some effect on their company’s EBIT, roughly the same share as a year earlier. The 6 percent figure uses a narrower threshold: at least 5 percent of EBIT attributed to AI. The results were reported by The Register and TechTimes, as cited by ThorstenMeyerAI.com.
BCG’s survey points to a similar gap between adoption and scale: 5 percent of 1,250 firms said they had achieved value at scale, while 60 percent reported no material value. These are survey results, not a single audited measure across companies, and the organizations use different definitions of value and performance.
AI use is growing in Europe, too. Eurostat reported that 20 percent of EU enterprises with at least 10 employees used AI in 2025, up from 13.5 percent in 2024. Use varied by company size: 55 percent among large enterprises and 17 percent among small ones. The adoption figures describe whether firms use AI, not whether it has improved their profits, a distinction also reflected in reports that AI delivers zero financial payoff to most companies.
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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From AI Pilots to Profit
The difference between using AI and earning a return matters to companies deciding where to spend on software, data and staff. The surveys suggest that deploying a chatbot or running separate pilots is not, on its own, evidence of business value. The article’s central finding is that firms reporting stronger results tend to focus on changing an entire workflow rather than adding AI to one step.
That can mean letting a system sort incoming cases, check records and prepare an action, with a person handling exceptions and overseeing the result. Such systems may reduce repetitive work, but they also require clear limits, reliable data and accountability for decisions. Without those, automation can add costs or create risks rather than produce measurable gains.
The shift also affects workers. In McKinsey’s survey, 80 percent of respondents who use AI said it made them more productive. At the same time, 39 percent expected job cuts, up from 32 percent in the previous survey. The source reports that earlier expected cuts exceeded cuts that had actually occurred; the survey does not establish how many future jobs will be affected.
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Adoption Outpaces Measured Returns
The analysis frames AI as a change in how work is done, not simply another software installation. Traditional digitization moved forms and records onto screens while people still interpreted cases and made decisions. AI systems can process some unstructured material, such as emails, invoices and support tickets, and take bounded actions after consulting other systems. That capability shifts the focus from selecting a tool to deciding which work can be safely redesigned.
Companies are also testing AI agents, systems that can take multiple steps rather than only retrieve information or generate a response. BCG respondents said agents accounted for about 17 percent of their AI value and expected the share to reach 29 percent by 2028. McKinsey reported that 40 percent of companies with more than $1 billion in revenue said they were scaling agents, compared with 27 percent previously. These are survey findings and expectations, not guarantees of future returns.
Barriers remain. Eurostat data cited in the article show that among European firms that considered AI but did not use it, 71 percent cited a lack of expertise. Gartner forecasts that more than 40 percent of agentic AI projects could be canceled by the end of 2027 because of costs, unclear value or weak risk controls. Gartner also forecasts that organizations will abandon 60 percent of AI projects that lack AI-ready data. Both figures are forecasts, not reported cancellation outcomes.
“The new promise is not “digitise the process” but “let software process the work.””
— Thorsten Meyer, ThorstenMeyerAI.com
Profit Measures Remain Uneven
The survey figures cannot be treated as one directly comparable scorecard. McKinsey and BCG asked different questions and used different definitions of high performance, value and scale. The source article cites published reports but does not provide enough methodological detail to reconcile the results or establish that AI caused the reported financial effects.
It is also unclear how much of the expected agent growth will translate into profit, how many projects will be canceled, or what employment effects will follow. Gartner’s cancellation numbers are forecasts, and workers’ expectations about job cuts are not job-loss counts. Company-level returns will depend on use case, implementation costs, data quality and human oversight.
Watch for Scaled Deployments
The next test is whether companies can turn pilots into sustained changes to core operations and report the costs and benefits clearly. Relevant indicators include whether deployments are used across a workflow, whether exceptions are handled safely, and whether measured savings or revenue gains exceed implementation and oversight costs.
Gartner’s cited forecast places potential agent-project cancellations by the end of 2027, while BCG respondents expect agents’ share of AI value to rise by 2028. Those dates provide milestones for comparing predictions with actual outcomes. For now, the available survey evidence supports a narrower conclusion: AI use is expanding, but broad adoption has not yet produced substantial, reported profit effects for most firms.
Key Questions
How many companies report substantial profit gains from AI?
In the McKinsey 2026 survey cited by the source article, 6 percent qualified as high performers, with at least 5 percent of EBIT attributed to AI. BCG separately found that 5 percent of surveyed firms said they were getting value at scale.
Does widespread AI use mean companies are making money from it?
No. Eurostat found that 20 percent of EU enterprises with at least 10 employees used AI in 2025, but that adoption measure does not show whether the companies made a profit from it. Survey results cited in the article show a much smaller share reporting substantial or scaled value.
What do companies need to do to get more value from AI?
The analysis points to redesigning workflows rather than adding AI to isolated tasks, choosing measurable use cases and setting controls for systems that can take actions. Reliable data and staff expertise are also reported as barriers.
Will AI agents replace workers?
The source material does not establish how many jobs will be replaced. McKinsey respondents reported higher expectations of job cuts, while 80 percent of AI users said the technology made them more productive. Expectations are not the same as confirmed job losses.
Source: ThorstenMeyerAI.com
