🔍 Read the full analysis: AI Adoption Is High, But Profits Remain Rare on ThorstenMeyerAI.com
Prime made for students and young adults
- Fast, free delivery for dorm and study essentials
- Prime Video and Amazon Music included
- Member-only deals
TL;DR
AI use is spreading, but surveys cited in a November 6 report find that substantial profit gains remain uncommon. McKinsey reported that 6% of surveyed respondents’ organizations qualified as AI high performers, while BCG found 5% of firms in its survey were getting value at scale. The figures reflect different surveys and definitions, and do not establish that AI caused companywide profit changes.
The report says 37% of respondents in McKinsey’s 2026 survey of 1,719 people 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, according to the report’s account of coverage by The Register and TechTimes. The 6% high-performer figure uses a narrower measure: organizations attributing at least 5% of EBIT to AI.
BCG’s survey of 1,250 companies found a comparable divide using its own criteria: 5% were getting value at scale, while 60% reported no material value. These results are not identical measures and should not be treated as a single, directly comparable estimate. They do, however, point to a recurring gap between companies adopting AI and companies reporting significant business returns.
Adoption is also increasing in Europe. Eurostat data cited in the report show that 20.0% of EU enterprises with at least 10 employees used AI in 2025, up from 13.5% in 2024. The reported rate was 55% among large enterprises and 17% among small ones. Those figures measure reported use, not whether AI improved profits.
Some companies are moving from chat-based tools toward AI agents, which can take a sequence of actions within set limits. The report says BCG respondents attributed about 17% of their AI value to agents and expected that share to reach 29% by 2028. McKinsey’s survey, as reported by The Register and TechTimes, found that 40% of companies with more than $1 billion in revenue said they were scaling agents, compared with 27% previously.
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.
Powered by Thorsten Meyer AI
Adoption Has Not Closed the Profit Gap
The findings matter because rising use alone does not show that AI is improving a company’s financial performance. For executives, the gap suggests that buying tools or running pilots is not enough: firms need to identify measurable outcomes and connect AI to work that affects costs, revenue or service quality. The surveys do not prove that a particular implementation strategy will produce profit, but they show that reported gains remain concentrated in a small minority.
The shift toward agents also changes the practical stakes. A tool that interprets documents, checks records and takes actions can affect whole workflows, not just the time a worker spends drafting or searching. That can bring operational benefits, but it also makes permissions, review of exceptions and accountability part of the implementation itself. Companies need to know what an agent may do and who is responsible for its results.
For employees, the evidence is mixed rather than conclusive. The report says 80% of McKinsey respondents who used AI reported productivity improvements. At the same time, 39% expected job cuts, up from 32% in the prior survey. Expectations are not confirmed layoffs, and the report says cuts in the previous year fell short of what respondents had anticipated. The figures describe perceptions among survey respondents, not a measured economy-wide employment effect.
Popular right now
KitchenAid Artisan 5-Quart Tilt-Head Stand Mixer, Almond Cream
Bose QuietComfort True Wireless Earbuds with Active Noise Cancellation, Black
Ninja NC501 CREAMi XL Deluxe 11-in-1 Ice Cream and Frozen Treat Maker
As an affiliate, we earn on qualifying purchases.
From Digitized Tasks to Automated Workflows
The report frames the change as a move beyond conventional digital transformation. In many earlier projects, software stored information or routed tasks while people continued to interpret cases and make decisions. AI systems can now work with unstructured material, such as emails or invoices, and may classify a case, retrieve information and take a limited action.
That capability does not mean every process is ready for automation. The report cites Gartner guidance distinguishing agents for situations requiring decisions, conventional automation for routine workflows, and assistants for simple information retrieval. It also says Gartner has warned that adding agents to legacy systems can be technically complex and disrupt existing workflows. BCG’s survey similarly points to end-to-end workflow redesign, rather than isolated pilots, as a path associated with greater reported value.
There are signs of changing technology decisions as well. The report says nearly a third of respondents’ organizations in McKinsey’s 2026 survey decided against buying at least one software product or feature because they believed they could build it in-house using agentic coding tools. This is a reported survey finding, not evidence that companies broadly are replacing commercial software with internally built systems.
Eurostat’s adoption figures offer a separate view of the trend in Europe. In 2025, large enterprises were substantially more likely than small enterprises to report AI use. Among European firms that had considered AI but did not use it, 71% cited a lack of expertise, according to the source report’s account of Eurostat data. The figures suggest an adoption and capability gap, but do not specify which skills or investments would resolve it.
Survey Measures Leave Key Questions Open
The survey findings rely on different samples, questions and definitions of value. The 37% figure refers to respondents saying AI had some effect on company EBIT; the 6% figure uses a threshold of at least 5% of EBIT attributed to AI. BCG’s “value at scale” and “no material value” categories use a separate framework. The results therefore cannot be combined into one adoption-to-profit rate.
The cited material does not establish how much of any reported financial effect was caused by AI rather than other changes, or how the results vary by industry and type of use. It also does not provide enough detail here to assess how respondents’ estimates were verified. The report’s forecasts about agent projects and AI-ready data remain projections, and actual outcomes may differ.
Employment effects are also unresolved. Respondents’ expectations of job cuts do not confirm that cuts will happen, while reported productivity gains do not show how those gains will affect staffing, wages or workloads over time. The available figures describe survey responses, not a final accounting of AI’s effect on workers.
Execution Will Test the Forecasts
The next test is whether companies can turn experiments into operating changes with clear measures of value. The source report says BCG respondents from leading companies had deployed 62% of their AI initiatives, compared with 12% among lagging firms. That comparison is reported by BCG and does not, on its own, show that deployment caused superior financial performance.
Gartner’s forecast places a near-term checkpoint on agent projects: it expects more than 40% to be cancelled by the end of 2027, citing costs, unclear value and weak risk controls. The report also points to AI-ready data and missing expertise as barriers. Whether those forecasts are borne out will depend on how companies manage costs, integrate systems and set limits on automated actions.
For now, the strongest confirmed takeaway is the contrast between expanding use and limited reported profit impact. Further survey results and company disclosures should clarify whether organizations can move beyond pilots, quantify returns consistently and explain how AI changes work. Until then, adoption rates, expectations and reported benefits should remain distinct measures.
Key Questions
How many companies are seeing substantial AI profit gains?
In the figures cited, 6% of respondents’ organizations in McKinsey’s 2026 survey qualified as high performers by attributing at least 5% of EBIT to AI. BCG separately found that 5% of surveyed companies were getting value at scale. The surveys use different definitions.
Does widespread AI use mean companies are making more money?
No. The report distinguishes adoption from financial results. Eurostat found that 20.0% of EU enterprises with at least 10 employees used AI in 2025, while the cited company surveys found substantial or scaled value was reported by a much smaller share.
What is an AI agent in this report?
An AI agent is described as a system that can take multiple steps, such as reading an incoming document, checking information in other systems and carrying out an action within defined limits. It differs from a tool that only retrieves information or drafts a response.
Why do AI projects fail to deliver value?
The report cites costs, unclear business value, weak risk controls, legacy-system complexity and a lack of AI-ready data. Eurostat data cited in the report show that 71% of European firms that considered AI but did not use it named missing expertise as a barrier.
Does the evidence show that AI is causing job losses?
Not conclusively. The report says 39% of McKinsey respondents expected job cuts, up from 32%, while 80% of respondents who used AI said it improved their productivity. Expectations and self-reported productivity do not establish how many jobs AI has eliminated.
Source: ThorstenMeyerAI.com
