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TL;DR
A McKinsey survey of 1,719 respondents found that 6% said their companies were high performers, attributing at least 5% of EBIT to AI. BCG reported a similar divide: 5% of 1,250 companies said they were generating value at scale, while 60% reported no material value. The findings point to workflow redesign, clear measures of value and risk controls as factors separating scaled efforts from pilots, though the surveys do not establish why any individual company succeeds or fails.
Only 6% of respondents in McKinsey’s 2026 survey said their companies generated at least 5% of earnings before interest and taxes (EBIT) from AI, according to the findings as reported by The Register and TechTimes. The result highlights a gap between companies using AI and those reporting sizable profit gains, while a separate BCG survey found just 5% of 1,250 companies were getting value from AI at scale.
McKinsey surveyed 1,719 respondents. In the report’s findings, 37% said AI had some effect on their company’s EBIT, about the same share as a year earlier. The 6% figure refers to a narrower group it classifies as “high performers”: respondents who said at least 5% of EBIT was attributed to AI. It does not mean that only 6% of companies use AI, or that the remaining companies had no benefit at all.
BCG’s survey of 1,250 firms found a comparable concentration of results: 5% said they were generating value from AI at scale, while 60% reported no material value. The two studies use their own definitions and survey populations, so their figures are similar indicators of a gap, not a direct, like-for-like measurement of the same companies.
AI use is spreading, including the use of systems called agents that can take steps toward completing tasks rather than only respond to prompts. McKinsey data reported by The Register and TechTimes said that among companies with more than $1 billion in revenue, 40% reported scaling agents, up from 27%. BCG respondents said agents accounted for about 17% of their AI value and expected that share to reach 29% by 2028; those figures reflect survey responses and expectations, not a verified forecast of future results.
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 Adoption Has Not Equaled Profit
The figures matter because AI spending and adoption do not, by themselves, show that a company is improving its financial performance. Executives, workers and investors looking at claims about AI need to distinguish between an organization testing tools, one using them in routine work, and one that can attribute a measurable business result to them. The surveys suggest that the last category remains much smaller than the first.
The source article points to redesigning whole workflows as a difference between isolated pilots and broader value. For example, a company might use AI to read an invoice, compare it with a contract and flag exceptions, rather than simply add a chatbot to a process that still requires staff to handle every step. That approach may involve changes to systems, responsibilities and oversight—not just buying a new tool. The survey findings are consistent with that argument, but do not prove that workflow redesign alone causes higher returns.
There are consequences for employees as well. McKinsey respondents who use AI reported productivity gains: 80% said it made them more productive. At the same time, 39% expected job cuts, up from 32% in the prior survey, according to The Register and TechTimes. Expectations are not evidence that cuts have happened at the same rate. The source reports that cuts in the previous year fell well short of respondents’ expectations.
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Adoption Is Growing at Uneven Speeds
Official European figures provide a different measure from the corporate surveys. Eurostat reported that 20.0% of EU enterprises with at least 10 employees used AI in 2025, up from 13.5% in 2024. Use varied by company size: 55% of large enterprises and 17% of small enterprises reported using AI. These adoption numbers do not measure profit or show whether a company had moved beyond experimentation.
The source article also cites a common obstacle for European firms that had considered AI but were not using it: 71% named a lack of expertise. That points to a capability gap, though the cited figure does not show whether skills shortages were the only barrier or how firms defined the expertise they lacked.
Forecasts suggest some pilots may not survive. Gartner predicts that more than 40% of agentic AI projects will be cancelled by the end of 2027 because of cost, unclear value or weak risk controls. It also forecasts that organizations will abandon 60% of AI projects that lack AI-ready data. These are Gartner forecasts, not completed cancellations. The source material does not provide the underlying forecast methodology or project counts.
“6% qualify as “high performers” with at least 5% of EBIT attributed to AI.”
— McKinsey survey findings, as reported by The Register and TechTimes
What the Survey Figures Cannot Show
The available figures are largely survey responses and forecasts. They do not establish that AI caused a reported change in EBIT, nor do they offer a single consistent measure of “value” across McKinsey and BCG. The source material does not provide full survey questionnaires, response rates or detailed methods for comparing results across studies.
It is also unclear which specific industries, AI systems or workflow changes account for the high performers’ reported results. The surveys describe broad patterns, but do not show whether companies with better outcomes had stronger data, more capable staff, different business models or other advantages. Gartner’s cancellation forecasts remain predictions, and the projected share of AI value from agents by 2028 has not yet been observed.
The Next Test Is Measurable Scale
The next measure of progress will be whether companies can move beyond pilots and show repeatable results in defined workflows. That means tracking costs and outcomes against a clear baseline, setting limits on what agents can do, and assigning people responsibility for reviewing exceptions. The source article describes these as practical priorities; it does not report a new policy or a universal standard for measuring AI returns.
By the end of 2027, Gartner’s forecast on agentic AI project cancellations will provide one marker of how many initiatives companies decide are too costly, risky or unclear in value. BCG respondents’ expectation that agents’ share of AI value will rise to 29% by 2028 offers another claim to test against later results. Until those milestones arrive, the 6% and 5% survey findings are snapshots of reported performance, not a final verdict on AI’s long-term business impact.
Key Questions
Does the 6% figure mean only 6% of companies use AI?
No. It refers to respondents whose companies met McKinsey’s “high performer” threshold of attributing at least 5% of EBIT to AI. It is not an AI adoption rate.
What did the BCG survey find?
BCG’s survey of 1,250 companies found that 5% reported value from AI at scale, while 60% said they had no material value. Its definitions may differ from McKinsey’s, so the figures should not be treated as directly interchangeable.
Why might AI pilots fail to produce profit?
The source article argues that isolated tools may have limited impact if the wider workflow stays unchanged. It also cites Gartner’s forecast that projects may be cancelled because of cost, unclear value or weak risk controls. The cited surveys do not establish one cause for every failed project.
Are AI agents already delivering value?
BCG respondents said agents accounted for about 17% of AI value and expected that share to reach 29% by 2028. These are reported and expected shares, not independently verified results for every company.
What is still unknown about AI’s effect on jobs?
McKinsey respondents’ expectations of job cuts rose to 39%, from 32%, but expectations do not establish how many jobs were or will be cut. The source material says prior-year cuts fell short of respondents’ expectations.
Source: ThorstenMeyerAI.com
