Most Companies Are Using AI. Few Are Earning From It
AIThis post was created with the assistance of artificial intelligence (AI).

🔍 Read the full analysis: Most Companies Are Using AI. Few Are Earning From It on ThorstenMeyerAI.com

Buying for a business?Offer from Amazon

Get business pricing on office and shipping supplies

  • Business-only prices and quantity discounts
  • Tax-exempt purchasing
  • Multiple users, one account, clear invoices
As an affiliate, we earn on qualifying purchases.

TL;DR

Surveys cited in a November 6 report show AI use has spread across companies, but meaningful financial returns remain concentrated among a small minority. McKinsey found 6% of respondents’ organizations attributed at least 5% of EBIT to AI; BCG found 5% of surveyed companies had achieved value at scale.

Most companies now use AI, but only a small minority report substantial financial returns, according to surveys and forecasts reviewed in a November 6 report by Thorsten Meyer. McKinsey’s 2026 survey found that 6% of respondents’ organizations met its definition of high AI performance, attributing at least 5% of earnings before interest and taxes (EBIT) to AI.

The figures vary by survey and by how each source defines success. In McKinsey’s survey of 1,719 respondents, 37% said AI had some effect on their organization’s EBIT, roughly unchanged from a year earlier. The figures were reported by The Register and TechTimes. The 6% high-performer figure refers to organizations attributing at least 5% of EBIT to AI; it is not a measure of all companies that use AI.

Boston Consulting Group’s survey of 1,250 companies found a similar gap: 5% said they were achieving value from AI at scale, while 60% reported no material value. Those results come from a separate survey with its own definitions, so they should not be treated as a direct comparison with McKinsey’s percentages.

Use is also uneven by company size and location. Eurostat reported that 20.0% of EU enterprises with 10 or more employees used AI in 2025, up from 13.5% in 2024. The 2025 rate was 55% among large enterprises and 17% among small enterprises. Those official EU figures measure adoption, not the financial return AI produced.

Company surveys also point to growing use of agents: AI systems that can take actions, rather than only generate responses. BCG respondents estimated agents delivered 17% of their AI value and expected that share to reach 29% by 2028. McKinsey figures 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%. These are survey findings and expectations, not audited measures of future returns.

At a glance
reportWhen: Published November 6, 2026; survey and…
The developmentA November 6 report comparing company surveys and forecasts finds broad AI adoption but limited evidence of substantial profit gains.
Thorsten Meyer AI
The value gap

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.

The number to remember6%

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

  • Used at least one AI technologyEU firms with 10+ staff, 2025 (Eurostat)20.0%
  • Report some EBIT effect from AIMcKinsey 2026 respondents37%
  • Scaling, some returnsBCG 2025 companies35%
  • No material value yetBCG 2025 companies60%
  • Value at scale (“future-built”)BCG 2025 companies5%
55%of large EU enterprises used AI in 2025 (small: 17%)
40%of $1B+ company respondents scale AI agents (27% a year earlier)
17%of AI value already comes from agents, BCG respondents say (29% expected by 2028)
80%of McKinsey respondents who use AI say it raised their productivity

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 Adoption Is Outpacing Returns

The gap matters because buying or testing AI is not the same as improving a company’s finances. The figures suggest that adoption alone does not establish business value: a company can deploy tools without changing costs, revenue or the way work gets done. That makes decisions about which projects to fund, how to measure results and when to stop a pilot more consequential for executives and investors.

The shift described in the report is from digitizing information to delegating parts of a workflow. AI may read an invoice, compare it with a contract, identify an exception and prepare a response, with a person reviewing the cases that need judgment. If a system takes action, companies must also define permissions, oversight and responsibility. Errors can affect customers, payments and staff, so efficiency claims need to be considered alongside controls.

Employees may see both productivity gains and disruption. In the McKinsey survey, 80% of respondents who use AI said it made them more productive. At the same time, 39% expected job cuts, up from 32% in the previous survey. These are respondents’ reports and expectations, not a count of confirmed layoffs. The report says last year’s job cuts fell short of what respondents had expected.

As an affiliate, we earn on qualifying purchases.

From Digital Tools to Workflow Agents

For many years, business technology mainly moved existing work onto digital systems: paper forms became online forms, and records moved into databases. People still read each case, made decisions and took action. The report argues that AI changes this division by allowing software to handle some interpretation and action, subject to rules and human review.

That distinction affects how companies should approach implementation. Gartner’s guidance, as summarized in the source report, differentiates agents for work requiring decisions, automation for routine processes and assistants for straightforward information retrieval. Gartner also warns that adding agents to legacy systems can be technically complex and disrupt existing workflows; in some cases, it says companies should redesign workflows rather than simply attach new tools.

BCG likewise argues that larger returns come from changing core workflows end to end, rather than relying on isolated pilots. Its survey found that companies classified as AI leaders had deployed 62% of their AI initiatives, compared with 12% among laggards. These are reported survey results, not proof that deployment by itself caused the difference in value.

Adoption remains constrained by practical barriers. Gartner forecasts that more than 40% of agentic AI projects will be canceled by the end of 2027 because of costs, unclear value or weak risk controls. It also forecasts that organizations will abandon 60% of AI projects lacking AI-ready data. In Eurostat data cited by the report, 71% of EU firms that considered AI but did not use it named a lack of expertise as a barrier. These figures describe forecasts and survey responses, not project outcomes already recorded.

How Much Value AI Actually Creates

The cited surveys do not provide a single, directly comparable measure of AI’s financial impact. Their samples, questions and definitions differ, and some figures reflect respondents’ estimates rather than audited company accounts. The 6% McKinsey high-performer figure and BCG’s 5% achieving value at scale describe separate survey findings, not a shared ranking of all businesses.

It is also unclear how much of the reported productivity improvement will translate into lasting profit, or how AI-related job expectations will compare with actual employment changes. The source material does not establish that agents will deliver the forecast share of AI value by 2028, or that projects Gartner expects may be canceled have already failed. Outcomes will depend on implementation, data quality, costs and controls.

What Companies Will Measure Next

The next test for companies is whether AI projects produce measurable results beyond adoption and employee usage. That means setting a baseline for costs, output or service quality, tracking changes over time and accounting for the expense of software, data preparation and human review. The report points toward selecting a small number of use cases, redesigning workflows where needed and assigning people to supervise decisions and exceptions.

Gartner’s cancellation forecasts put project value, data readiness and risk controls in focus through 2027. BCG’s survey respondents expect agents’ share of AI value to rise by 2028, but that remains a reported expectation. Further evidence will be needed to show whether companies can turn agent deployment into sustained financial returns—and how those changes affect employees.

Key Questions

How many companies are making substantial profits from AI?

In McKinsey’s 2026 survey, 6% of respondents’ organizations met its high-performer definition by attributing at least 5% of EBIT to AI. BCG separately found that 5% of surveyed companies were achieving value at scale. The surveys use different methods and definitions.

How widely is AI used 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% in 2024. Usage was 55% among large enterprises and 17% among small ones.

What is an AI agent in this report?

An AI agent is a system that can take steps toward completing a task, such as reading a document, looking up related information and preparing or carrying out an action within set limits. The report distinguishes agents from assistants that mainly retrieve information.

Why do companies struggle to get value from AI?

The cited sources point to unclear business value, cost, weak risk controls, poor data readiness and missing expertise. Gartner also warns that adding agents to older systems can disrupt workflows, while BCG argues that companies may need to redesign processes rather than add isolated pilots.

Does the report show that AI is causing job cuts?

No. McKinsey survey respondents were more likely to expect job cuts—39%, up from 32%—but those expectations are not confirmed layoff totals. The source report says cuts in the prior year fell short of what respondents had anticipated.

Source: ThorstenMeyerAI.com

This content is for general information only and is not financial, tax or legal advice. Consult a qualified professional for decisions about your money.
You May Also Like

How My Book Helps Make Sense Of This Month’s AI Headlines

Thorsten Meyer’s new ebook uses recent headlines on agents, jobs, prices and investment to explain six ways to evaluate AI claims.

The Fine Line Between AI Accuracy And Effective Management

A recent experiment reveals that AI models can understand business crises but often fail to complete trustworthy, actionable work under pressure. Why this matters.

OpenAI Dev Day 2026: A Tour Of The Key Announcements

OpenAI used DevDay on Sept 29, 2026 to announce 20+ products, including Dots agents, upgraded plugins, a Decisions API and GPT-6.1 Sol.

From Sensors To Software Autonomy: AI’s Transformative Power

New developments show European agencies contracting for independent ISR software, marking a shift toward sovereignty in sensor-to-software AI systems.