🔍 Read the full analysis: How Companies Can Bridge The AI Adoption-to-Profit Gap on ThorstenMeyerAI.com
Get business pricing on tech for your team
- Business-only prices and quantity discounts
- Tax-exempt purchasing
- Multiple users, one account, clear invoices
TL;DR
Corporate AI use is growing, but surveys cited by ThorstenMeyerAI.com suggest only a small share of companies can attribute substantial earnings gains to it. The analysis points to workflow redesign, focused use cases, measurable outcomes and controls for AI agents as ways to narrow the gap; Gartner forecasts that many projects without clear value or suitable data will be abandoned.
A November 6 analysis of corporate AI research finds that adoption has spread much faster than measurable profit gains, with just 6% of respondents in McKinsey’s 2026 survey qualifying as high performers who attribute at least 5% of earnings before interest and taxes to AI. The figures underline a practical challenge for companies: getting value often requires redesigning whole workflows, rather than adding AI tools to existing steps.
McKinsey’s 2026 survey included 1,719 respondents; 37% said AI had some effect on their company’s EBIT, about the same share as a year earlier. The 6% high-performer figure, reported by The Register and TechTimes, uses a more demanding threshold: at least 5% of EBIT attributed to AI. It is not a measure of how many companies use AI.
A separate Boston Consulting Group study of 1,250 companies found a similar divide: 5% said they were generating value from AI at scale, while 60% reported no material value. These are survey findings, not audited financial results, and the studies use their own definitions of adoption and value.
AI agents — systems that can take steps within assigned limits, rather than only answer prompts — are becoming part of the discussion. BCG respondents attributed about 17% of 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, up from 27%.
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
Why AI Projects Miss the Profit Test
The adoption-profit gap matters because buying software or launching pilots does not, by itself, change how work gets done. The analysis argues that stronger returns come when companies redesign an end-to-end process — such as handling invoices, support requests or contract checks — and decide which steps AI can perform, which require human review, and how outcomes will be measured.
That approach also changes accountability. When an agent can retrieve information, draft a response or take an action, a company needs clear permissions, records of what happened, and a person responsible for exceptions. Without those arrangements, apparent speed gains may be offset by errors, added oversight or risk. The source cites Gartner guidance that agents fit tasks requiring decisions, conventional automation suits routine workflows, and assistants can serve simple information retrieval.
For employees, the evidence is mixed. 80% of McKinsey respondents who use AI said it made them more productive, while 39% expected job cuts, up from 32% in the previous survey. The report also says past cuts fell short of respondents’ earlier expectations. Those figures reflect survey responses and expectations, not a confirmed forecast of employment outcomes.
Products Worth Considering
Logitech MX Keys Combo for Business Keyboard and Mouse – Graphite
Samsung Galaxy Tab A11 8.7-Inch Wi-Fi Tablet, 64GB, 4GB RAM, Silver
Anker SOLIX S2000 Portable Power Station, 2,010Wh, 1,500W
As an affiliate, we earn on qualifying purchases.
Adoption Varies Across Europe
Official Eurostat data show that 20.0% of EU enterprises with at least 10 employees used AI in 2025, up from 13.5% in 2024. Adoption was reported by 55% of large enterprises and 17% of small enterprises. This measure provides a separate view from global company surveys: it tracks reported use, not whether AI increased profits.
The analysis says firms that considered AI but did not adopt it most often cited a lack of expertise; 71% of that group gave this reason, according to the Eurostat figures it references. That suggests capability constraints remain part of the adoption picture, even as attention shifts toward whether deployments produce financial returns.
The research also points to a change in the usual digital-transformation model. Earlier programmes often moved existing tasks onto software while people continued to interpret information and make decisions. AI systems can handle some unstructured inputs and carry out bounded actions, but the source’s central argument is that businesses need to rethink the workflow, not simply insert a new tool into the old one.
What the Surveys Cannot Establish
The cited figures do not establish that AI caused a particular company’s profit change. They come from surveys with differing samples, definitions and thresholds, and the source reports them through secondary coverage in several cases. The figures should not be treated as directly comparable or as audited financial data.
It is also unclear how many companies can sustain reported gains over time, which specific deployments account for them, or how much value remains after implementation and supervision costs. Gartner’s forecasts are projections, not confirmed outcomes: it predicts that more than 40% of agentic AI projects could be cancelled by the end of 2027 because of cost, unclear value or weak risk controls, and that organisations will abandon 60% of AI projects that lack AI-ready data.
Measuring Results Through 2027
Companies will need to test whether AI projects improve a defined business measure, such as processing time, error rates or operating costs, and compare results with a clear baseline. The analysis recommends focusing on a limited number of use cases, changing the workflow where needed, and setting rules for what agents may do before expanding deployment.
The next indicators will be whether reported agent rollouts translate into sustained financial results and whether projects address data quality, expertise and governance gaps. Gartner’s cancellation forecast runs through the end of 2027; the source provides no confirmed company-by-company outcomes or timetable for when the surveyed firms will report further financial effects.
Key Questions
How many companies report substantial profit gains from AI?
In McKinsey’s 2026 survey, 6% of respondents’ organisations met its high-performer definition: at least 5% of EBIT attributed to AI. This is a survey result, not an audited count of companies.
Does widespread AI use mean companies are earning more?
No. The cited surveys show adoption and reported financial effects are different measures. McKinsey found that 37% said AI had some effect on EBIT, while BCG reported that 60% of surveyed companies had no material AI value.
What changes can help companies get more value from AI?
The analysis recommends redesigning end-to-end workflows, choosing focused use cases, tracking results against defined measures, and setting permissions and human review for AI agents.
Will AI agents replace workers?
The cited evidence does not establish how many jobs agents will replace. McKinsey respondents reported productivity gains among AI users and greater expectations of job cuts, but those expectations are not confirmed employment outcomes.
Why might AI projects be cancelled?
Gartner forecasts that more than 40% of agentic AI projects could be cancelled by the end of 2027 because of cost, unclear value or weak risk controls. It also forecasts abandonment of 60% of AI projects that lack AI-ready data.
Source: ThorstenMeyerAI.com
