🔍 Read the full analysis: AI Is Everywhere In Business, But Profits Are Not on ThorstenMeyerAI.com
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TL;DR
Surveys cited in a November 6, 2026, report show a gap between growing business use of AI and measurable financial returns. McKinsey found 6% of respondents’ organizations met its definition of AI high performers, while BCG found 5% of surveyed companies were getting value at scale; the results are survey findings, not a measure of every company’s performance.
Business use of AI is expanding faster than reported profit gains, according to a November 6 report drawing on surveys from McKinsey and Boston Consulting Group (BCG), alongside European Union data and industry forecasts. 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.
McKinsey surveyed 1,719 respondents; 37% said AI had some effect on their organization’s EBIT, about the same share as a year earlier, according to the report’s accounts of the survey published by The Register and TechTimes. The 6% figure uses a narrower threshold: those organizations attributed at least 5% of EBIT to AI. The findings reflect respondents’ reports and definitions, rather than independently audited returns across all businesses.
BCG’s study of 1,250 companies found a similar concentration of reported results: 5% were getting value from AI at scale, while 60% reported no material value. The report says BCG respondents attributed about 17% of their AI value to agents and expected that share to reach 29% by 2028. Agents are systems designed to carry out steps toward a task, rather than only generate responses. These figures are survey findings and expectations, not guarantees of future performance.
AI use also varies by company size and region. Eurostat data cited in the report show that 20% of EU enterprises with at least 10 employees used AI in 2025, up from 13.5% in 2024. The reported rate was 55% for large enterprises and 17% for small ones. In McKinsey’s survey, 40% of companies with more than $1 billion in revenue said they were scaling AI agents, up from 27%, according to The Register and TechTimes.
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 Returns Remain Uneven
The gap matters because companies may be moving from software that helps employees handle tasks to systems that can perform parts of a workflow. That change could affect costs, speed and how work is divided, but adoption alone does not show that those benefits have reached the bottom line. The surveys suggest that reported financial value remains concentrated, even as use spreads.
The source report argues that stronger results are associated with redesigning whole workflows rather than adding AI to isolated tasks. BCG’s survey findings support that distinction: the report says leading companies had deployed 62% of their AI initiatives, compared with 12% among laggards. This is a reported relationship, not proof that deployment alone caused better results. Company size, sector, data quality and how “value” is defined may also shape the figures.
For employees, the survey picture is mixed. The report says 80% of McKinsey respondents who use AI reported productivity improvements. At the same time, 39% expected job cuts, up from 32% previously. The report also says earlier expectations of cuts exceeded the reductions that occurred. These are respondents’ perceptions, not a forecast that a particular workforce will grow or shrink.
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From Digitized Tasks to AI Agents
The report frames AI as a change from digitizing existing processes to having software handle parts of the work itself. Earlier transformation projects often moved forms and records into digital systems while people continued to review cases and make decisions. AI tools can process some unstructured material, such as emails, invoices and support tickets, then retrieve information or take permitted actions.
That shift makes workflow design and oversight central to a deployment. The report attributes to Gartner guidance that agents are suited to tasks requiring decisions, while conventional automation is better for routine workflows and assistants for simple information retrieval. It also cites Gartner’s warning that adding agents to older systems can be technically complex and disruptive, and says redesigning workflows may be preferable in some cases.
Adoption remains limited by practical barriers. Eurostat figures in the report show that among EU firms that considered AI but did not use it, 71% cited a lack of relevant expertise. The report also cites Gartner forecasts that more than 40% of agentic AI projects could be canceled by the end of 2027 because of costs, unclear value or weak risk controls, and that 60% of AI projects without AI-ready data could be abandoned. These are forecasts, not confirmed cancellation rates.
What the Surveys Cannot Establish
The cited surveys do not establish that AI caused a specific company’s profit change. They use different samples and measures: the McKinsey result concerns respondents’ reports of effects on EBIT, while BCG reports companies’ assessments of value at scale. The figures should not be treated as directly comparable or as audited accounts of business-wide returns.
It is also unclear from the source material how results vary across industries, which AI systems generated the reported gains, or how companies calculated the share of EBIT attributed to AI. The forecast cancellation rates are estimates, while the expected rise in agents’ contribution to AI value is a projection. Actual outcomes may differ.
Tracking Results Beyond the Pilot
The next test for companies will be whether pilots become measured, sustained changes to business operations. The report’s evidence points to practical questions: whether the underlying data are usable, whether a workflow has been redesigned, and whether staff can review exceptions and take responsibility for actions. Companies adopting agents also need to set permissions and maintain records of what systems do.
Gartner’s cited forecasts put pressure on organizations to show clear value and adequate controls before expanding projects, particularly as possible cancellations rise through 2027. The source report does not identify a single upcoming release or deadline that will settle whether AI is improving profits across business. Future surveys and company results will be needed to show whether reported productivity gains translate into broader, sustained financial returns.
Key Questions
Are most companies making money from AI?
The cited surveys do not show that most companies are earning substantial returns. McKinsey found 6% of respondents’ organizations met its high-performer definition, while BCG reported that 5% of surveyed companies were getting value at scale. Those measures are not identical.
What does McKinsey mean by an AI high performer?
In the survey described in the report, a high performer is an organization attributing at least 5% of EBIT to AI. The report says 6% of respondents’ organizations met that threshold.
What are AI agents?
In the report, agents are AI systems that can take steps toward completing a task, such as processing information and acting within set limits, rather than only answering a prompt. Their actions require appropriate permissions and oversight.
Why do AI projects fail or get canceled?
The report cites Gartner forecasts identifying cost, unclear business value and weak risk controls as reasons agentic AI projects may be canceled. It also cites a forecast that projects without AI-ready data may be abandoned. These are projections, not confirmed outcomes.
Does AI use mean jobs will be cut?
Not by itself. The report says 39% of McKinsey respondents expected job cuts, up from 32%, but that is a survey response, not a measure of planned cuts at every company. It also says earlier expectations of cuts exceeded the reductions that occurred.
Source: ThorstenMeyerAI.com
