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TL;DR
Surveys cited by ThorstenMeyerAI.com show a persistent gap between companies using AI and those reporting material financial value. McKinsey’s 2026 survey found 6% of respondents’ organizations qualified as high performers, while BCG found 5% of surveyed companies were getting value at scale. The figures are survey findings, not proof that AI caused a particular company’s profits.
A November 6 report from ThorstenMeyerAI.com finds that companies are adopting AI far faster than they are reporting meaningful financial returns, based on surveys from McKinsey and Boston Consulting Group (BCG) and forecasts from Gartner. In McKinsey’s 2026 survey, 6% of respondents’ organizations met its definition of high performers, attributing at least 5% of earnings before interest and taxes (EBIT) to AI; the figures underline why adoption alone is not a measure of profitability.
McKinsey surveyed 1,719 respondents. According to the report’s summaries by The Register and TechTimes, 37% said AI had some effect on their organization’s EBIT, roughly the same share as a year earlier. That measure covers any reported effect, not necessarily a positive or independently verified gain. The smaller high-performer group was defined as organizations attributing at least 5% of EBIT to AI.
BCG’s study of 1,250 companies presents a similar divide: 5% said they were getting value from AI at scale, while 60% reported no material value. The source article does not provide enough detail here to treat the two firms’ measures as directly equivalent. Both results are survey responses, not audited financial statements establishing that AI alone produced the reported outcomes.
Adoption figures show why the gap matters. Eurostat reported that 20.0% of EU enterprises with 10 or more employees used AI in 2025, compared with 13.5% in 2024. The 2025 share was 55% among large enterprises and 17% among small ones. These figures measure reported use, not whether an organization made money from it.
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 difference between using AI and earning a return affects how companies should judge their technology spending. Installing a chatbot or adding an AI feature can increase adoption counts without changing costs, revenue or the time needed to complete work. The report’s central finding is that stronger value is associated with redesigning entire workflows, rather than placing AI on top of existing steps and measuring success by the number of pilots.
That shift also changes operational responsibilities. AI systems that read documents, retrieve information and take actions need clear permissions, records and human oversight for exceptions. A tool that can send messages or initiate transactions creates different risks from one that only drafts text. The source argues that governance must be part of implementation, while the surveys cited do not establish a universal formula for producing returns.
Employees face a mixed picture. In McKinsey’s survey, 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 previous survey, according to The Register and TechTimes. Those are respondents’ views, not a count of layoffs caused by AI; the source says prior job reductions fell short of expectations.
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Adoption Has Outpaced Proven Returns
The report frames AI as a shift from digitizing paperwork to having software process parts of the work. Traditional systems stored information and moved it between screens, while people interpreted cases and made decisions. Newer AI systems can handle unstructured inputs such as emails, invoices and support tickets, consult other systems and take actions within set limits. The change can reach beyond software selection into how a process is designed and supervised.
BCG respondents said AI agents supplied about 17% of their AI value and expected the share to reach 29% by 2028. McKinsey’s survey, as summarized 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-reported figures and expectations; they do not show that agents will deliver the forecast share in practice.
European adoption remains uneven by company size. Eurostat’s 2025 figures show a 38-percentage-point gap between large and small enterprises. Among businesses that had considered AI but did not use it, 71% cited missing expertise, according to the source article’s account of Eurostat data. That points to capability constraints alongside questions about cost and return.
“Use AI agents when decisions are needed, automation for routine workflows and assistants for simple retrieval.”
— Gartner, as quoted in ThorstenMeyerAI.com’s report
Survey Measures Leave Key Questions
The cited surveys use different questions and definitions, so their percentages should not be combined into a single measure of AI profitability. The source material does not provide the underlying survey questionnaires, company-level financial data or independent verification of respondents’ attributions. It is also unclear how much of the reported EBIT effect represents savings, new revenue or other factors occurring alongside AI adoption.
Gartner forecasts that more than 40% of agentic AI projects will be cancelled by the end of 2027 because of costs, unclear value or weak risk controls. It also forecasts that organizations will abandon 60% of AI projects that lack AI-ready data. These are forecasts, not completed cancellation counts. The source does not specify the total number of projects behind those percentages or provide enough detail to assess how they apply across industries.
More broadly, the evidence does not establish how many jobs will be cut, how many new roles will appear or whether productivity gains will translate into lasting profit. Those outcomes depend on how companies deploy the systems and what work they change.
Companies Face a Delivery Test
The next test is whether organizations can move beyond trials and show measurable results in live operations. The report points to a practical sequence: select a small number of valuable workflows, redesign them rather than simply adding a tool, set boundaries for what agents can do, and track financial and operational outcomes. BCG reported that its leaders had deployed 62% of their AI initiatives, compared with 12% among laggards, though the source does not establish that deployment alone caused the difference in value.
Companies will also need to address data readiness and staff expertise, while deciding where human review remains necessary. Gartner’s project-cancellation forecasts make cost, clear business value and risk controls immediate concerns for organizations planning agent deployments. The surveys described in the report do not give a single deadline for when firms will see returns.
Further evidence will depend on future survey results and company reporting that separates AI-related effects from other business changes. Until then, the available findings support a cautious conclusion: use is expanding, but consistent, material profit gains remain uncommon by the measures cited.
Key Questions
How many companies report substantial AI-driven profit gains?
In McKinsey’s 2026 survey of 1,719 respondents, 6% of organizations met its high-performer definition: attributing at least 5% of EBIT to AI. BCG separately reported that 5% of 1,250 surveyed companies were getting value at scale. The studies use different measures.
Does using AI mean a company is profitable from it?
No. Eurostat’s figures measure whether enterprises reported using AI, while the McKinsey and BCG findings cover reported effects or value. Adoption is not the same as financial return, and the cited surveys do not provide audited proof that AI caused specific profits.
Why do some AI projects fail to scale?
The source report points to unclear value, costs, weak risk controls, data that is not ready for AI and shortages of expertise. Gartner forecasts that more than 40% of agentic AI projects will be cancelled by the end of 2027, but that is a forecast, not a recorded outcome.
What does the report say about AI and jobs?
McKinsey respondents who used AI commonly reported productivity gains: 80% said it made them more productive. The share expecting job cuts rose to 39% from 32%, but expectations are not evidence that AI caused layoffs. The report says previous cuts fell short of what respondents had expected.
Source: ThorstenMeyerAI.com
