🔍 Read the full analysis: The Business Of AI: Usage Is Common, Profits Are Not on ThorstenMeyerAI.com
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TL;DR
Surveys cited in a November 6, 2026 report show AI use is spreading across companies, while substantial financial returns remain concentrated among a small minority. The sources point to workflow redesign, data readiness, expertise and governance as key factors in whether projects scale; forecasts about future cancellations are not confirmed outcomes.
AI use is spreading across businesses, but relatively few companies report a substantial contribution to profits, according to surveys and forecasts reviewed in a November 6 report by Thorsten Meyer. McKinsey’s 2026 survey found that 37 percent of respondents said AI affected their company’s EBIT, while 6 percent met its definition of high performers, attributing at least 5 percent of EBIT to AI.
The figures point to a gap between adopting AI and turning it into measurable financial value. In the McKinsey survey of 1,719 respondents, the share reporting some effect on EBIT was about the same as a year earlier. The results were reported by The Register and TechTimes. Separately, Boston Consulting Group’s study of 1,250 companies found that 5 percent were getting value from AI at scale, while 60 percent reported no material value, according to Meyer’s account.
The indicators measure different things and should not be treated as one combined estimate: one asks about AI’s effect on EBIT, while the other assesses value at scale. Adoption figures also vary by geography and company size. Eurostat reported that 20 percent of EU enterprises with at least 10 employees used AI in 2025, up from 13.5 percent. Use was reported by 55 percent of large enterprises and 17 percent of small ones.
Companies are also testing AI agents, systems that can take steps toward completing tasks rather than only responding to prompts. BCG respondents attributed about 17 percent of their AI value to agents and expected that share to reach 29 percent by 2028. McKinsey reporting cited by The Register and TechTimes said 40 percent of companies with revenue above $1 billion reported scaling agents, compared with 27 percent in the previous survey.
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 Spending Is Not Yet Paying Off
The gap matters because businesses are investing in tools that can affect both operating costs and how work is organised, but adoption alone does not establish a financial return. The survey results suggest that companies may have AI products in use without having changed enough of the underlying process to capture measurable gains. They are survey findings, not an independently verified accounting of every company’s results.
The report argues that more value may come from redesigning end-to-end workflows than from adding AI to isolated tasks. For example, software might classify an invoice, check it against a contract and flag an exception for a person. That could reduce routine handling, but it also requires clear limits, reliable data and accountability for decisions. The business case depends on whether those changes produce benefits that can be measured against their costs and risks.
There may also be consequences for employees. 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 previously. Those expectations are not evidence that cuts will occur at that rate: the report says reductions in the prior year fell short of what respondents had expected.
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From Digitising Tasks to Delegating Them
Earlier digital transformation efforts often moved records and forms from paper into software while leaving people responsible for interpreting each case and deciding what to do. AI systems can now handle some unstructured inputs, such as emails, scanned invoices and support tickets, and can retrieve information or take specified actions. The shift is from digitising a process to letting software perform parts of it.
The distinctions between AI assistants, automation and agents matter for implementation. The report attributes to Gartner guidance to use agents when decisions are needed, automation for routine workflows and assistants for simple information retrieval. An agent that can send a message or initiate a payment also needs defined permissions, logging and a way for people to intervene. Those controls are part of the work of deploying the system, not separate from it.
Companies face practical obstacles as they move from experiments to wider use. Eurostat data cited in the report found that among EU firms that had considered AI but did not use it, 71 percent cited a lack of relevant expertise. Gartner forecasts that more than 40 percent of agentic AI projects could be cancelled by the end of 2027 because of costs, unclear value or weak risk controls. It also forecasts that organisations will abandon 60 percent of AI projects that lack AI-ready data. These are forecasts, not recorded cancellation rates.
“80 percent of respondents who use AI said it made them more productive.”
— McKinsey survey respondents, as reported by The Register and TechTimes
What the Surveys Cannot Yet Show
The figures do not establish that AI caused a specific change in profits, productivity or employment across the companies surveyed. They reflect responses gathered under different definitions and survey methods; the reported adoption, EBIT impact and value-at-scale measures are not directly interchangeable. The source material does not provide enough detail to compare all survey samples or methods on a like-for-like basis.
It is also unclear how many current pilots will become sustained deployments, what returns those deployments will produce after costs, or how widely job effects will be felt. Gartner’s project-cancellation figures are forecasts, while survey respondents’ expectations about job cuts are expectations rather than confirmed outcomes. The share of value attributed to agents is reported as a survey estimate and an expectation, not a guarantee of future gains.
The Test Is Scaling With Controls
The next test for businesses is whether they can move selected AI projects into everyday operations and show measurable value. The report says stronger performers tend to focus on a smaller number of use cases, redesign workflows and track results, while also setting rules for what systems may do and when people must review their work. BCG reported that leading companies had deployed 62 percent of their AI initiatives, compared with 12 percent among laggards; the source does not specify a common deployment outcome for those initiatives.
Companies will also need to address data quality and staff expertise before expanding systems that make decisions or take actions. The Gartner forecasts identify data readiness, cost, unclear value and risk controls as potential reasons projects may be stopped. As deployments mature, further survey results and company disclosures will show whether broader use translates into sustained financial returns and how work changes in practice.
Key Questions
How many companies say AI affects their profits?
In McKinsey’s 2026 survey, 37 percent of respondents said AI had some effect on their company’s EBIT. Six percent qualified as high performers under the survey’s definition, which required at least 5 percent of EBIT to be attributed to AI.
Does widespread AI use mean companies are making money from it?
No. The survey results show that adoption and reported financial impact are different measures. BCG found 5 percent of the 1,250 companies it studied were getting value at scale, while 60 percent reported no material value.
What is an AI agent?
An AI agent is a system designed to take steps toward a task, such as reviewing information or carrying out an action within set limits, rather than only answering a question. The report says such systems require permissions, monitoring and human oversight.
Why do AI projects stall?
The report identifies missing expertise, data that is not ready for AI, unclear business value, costs and weak risk controls as barriers. Gartner’s stated project-cancellation figures are forecasts, not confirmed outcomes.
Does the report show that AI is causing widespread job cuts?
No. McKinsey survey respondents increasingly expected job cuts, but that expectation is not a record of actual layoffs. The source report says cuts in the previous year fell short of what respondents had anticipated.
Source: ThorstenMeyerAI.com
