🔍 Read the full analysis: A Guide To Turning Company AI Use Into Profit on ThorstenMeyerAI.com
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TL;DR
A Nov. 6 guide by Thorsten Meyer compares surveys and forecasts on corporate AI, finding that use is spreading faster than reported profit gains. The figures point to workflow redesign, measurable value and controls as key challenges, while the scale of AI’s effect on company profits remains difficult to establish.
Most companies are using AI somewhere, but few report substantial profit gains from it, according to a Nov. 6 guide by Thorsten Meyer that brings together surveys from McKinsey and Boston Consulting Group, European Union data and forecasts from Gartner. The findings highlight a gap between adoption and financial results as businesses weigh whether to redesign work around AI systems or continue with limited pilots.
In McKinsey’s 2026 survey of 1,719 respondents, 37% said AI had some effect on their company’s earnings before interest and taxes, or EBIT, a share Meyer says was about the same as the previous year. Just 6% were classed as “high performers”, meaning at least 5% of EBIT was attributed to AI, according to the survey as reported by The Register and TechTimes. These are survey responses, not independently audited measures of AI’s contribution to company earnings.
BCG’s study of 1,250 companies found a comparable divide: 5% said they were getting value from AI at scale, while 60% reported no material value. BCG respondents attributed about 17% of their AI value to agents and expected that share to reach 29% by 2028. McKinsey data, as reported by The Register and TechTimes, found that 40% of companies with more than $1 billion in revenue said they were scaling agents, up from 27%.
European adoption is growing from a lower base. Eurostat reported that 20.0% of EU enterprises with 10 or more employees used AI in 2025, up from 13.5%. The rate was 55% among large enterprises and 17% among small ones. Among companies that had considered AI but did not use it, 71% cited a lack of expertise, according to Eurostat figures included in Meyer’s guide.
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 AI Profit Gains Remain Limited
The figures matter because companies are making decisions about software spending, staffing and operating models while evidence of broad financial returns remains limited. Adoption is not the same as value: a company can use AI for isolated tasks without changing enough of its costs, output or revenue to affect its overall earnings.
Meyer’s account points to workflow redesign as a dividing line. BCG says its respondents see greater value in reshaping core workflows end to end than in running isolated pilots. The survey also found that leaders had deployed 62% of their AI initiatives, compared with 12% among laggards. The figures suggest an association between implementation and stronger results, but do not establish that deployment alone caused the difference.
For workers, the picture is mixed. 80% of McKinsey respondents who use AI said it made them more productive. At the same time, 39% expected job cuts, up from 32% a year earlier. Meyer notes that reported job cuts in the previous year fell short of what respondents had expected. The survey figures describe expectations and reported experience; they do not establish how AI will affect employment across the economy.
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From Digitized Tasks to AI Workflows
Earlier digital transformation programmes often moved paper-based processes into software while leaving people responsible for interpreting information and making decisions. Meyer argues that AI changes that model by allowing systems to read materials such as emails, invoices and support tickets, retrieve related information and take actions within assigned limits.
That shift puts the workflow, not just the software tool, at the centre of a transformation project. Meyer cites Gartner’s guidance to use AI agents when decisions are needed, conventional automation for routine workflows and assistants for simple information retrieval. Agents can take multiple steps, but their actions still need defined permissions and human oversight.
The guide also cites a Gartner forecast that more than 40% of agentic AI projects could be cancelled by the end of 2027 because of costs, unclear value or weak risk controls. Gartner separately forecasts that organisations will abandon 60% of AI projects that lack AI-ready data. These are forecasts, not confirmed cancellation rates. The source also says nearly a third of respondents’ organisations had decided against buying at least one software product or feature because they could build it in-house with agentic coding tools, according to McKinsey data reported by The Register.
“The new promise is not “digitise the process” but “let software process the work.””
— Thorsten Meyer, in the guide
What the Surveys Cannot Establish
The cited figures come from different surveys, populations and definitions of AI use and value, so they are not directly comparable. The material does not provide a common method for measuring AI’s contribution to profit across companies. In McKinsey’s results, the reported EBIT effect is based on respondents’ accounts; it is not presented here as an audited causal measure.
Gartner’s project-cancellation figures are forecasts, and BCG’s expected agent-value share by 2028 is a respondent expectation. It remains unclear how many projects will ultimately be cancelled, how many companies will reach sustained returns, or how AI-driven productivity will affect employment over time.
Measuring Results Beyond the Pilot
The next test for companies will be whether AI projects move from pilots into operational workflows with clear measures of cost, quality, speed or revenue. Meyer’s account points to selecting a small number of use cases, tracking results and setting controls over what agents can do. Those steps are recommendations in the guide, not a guarantee of profit.
Gartner’s forecast makes the period through the end of 2027 a key window for observing whether agentic AI projects are sustained or cancelled. BCG respondents expect agents to account for a larger share of AI value by 2028, but that remains a forecast. Further survey results and company-level reporting will be needed to show whether adoption produces durable financial gains.
Key Questions
In McKinsey’s 2026 survey, 6% of respondents’ organisations met its “high performer” definition: at least 5% of EBIT attributed to AI. The result reflects survey responses, not a universal or independently audited measure.
How widely is AI used by companies in the European Union?
Eurostat reported that 20.0% of EU enterprises with 10 or more employees used AI in 2025, compared with 13.5% previously. Adoption was 55% among large enterprises and 17% among small ones.
Why do some AI projects fail to deliver value?
The cited sources identify costs, unclear value, weak risk controls, lack of AI-ready data and limited expertise as barriers. BCG’s findings also point to a gap between isolated pilots and changes to complete business workflows.
What is an AI agent in this report?
An AI agent is a system that can take steps toward a task, such as classifying an invoice, checking information in other systems and acting within set limits. The guide says such systems need permissions, monitoring and human oversight.
Do the figures show that AI is causing job cuts?
No. The cited McKinsey survey says 39% of respondents expected job cuts, up from 32%, while reported cuts in the previous year fell short of expectations. Those figures do not establish that AI caused employment changes.
Source: ThorstenMeyerAI.com
