37% of firms see any profit from AI, 6% a real one, as agents spread

01Most users feel faster; few firms see it in profit

McKinsey’s 2026 survey covered 1,719 professionals and business leaders across regions and industries. 37% of respondents attribute at least some impact on EBIT (earnings before interest and taxes) to AI, about the same share as in the 2025 survey. McKinsey keeps a stricter group, the “high performers”: firms where AI accounts for at least 5% of EBIT and the respondent calls the impact significant. Just 6% of respondents meet both tests, the same as last year.¹

Productivity is where the survey looks good. 80% of respondents who use AI in their own roles say it has improved their individual productivity, and The Register notes that this has not turned into a broad financial effect.¹ These numbers come from different bases, which is why the chart shows them separately: the first is about people, the other two are about firms.

02Agents rose 13 points in a year; the profit share did not

Agents, AI that carries out multi-step tasks rather than answering a prompt, are where the money is going now. 40% of respondents at organisations with more than US$1 billion in annual revenue say they are scaling AI agents, against 27% a year earlier. Nearly a third of respondents say their organisations decided against buying one or more software products and built the function in-house with agentic coding tools instead.¹

The costs are now visible: 20% of respondents say AI operating costs have limited how much they use it. Expectations about jobs have moved too. 43% expect little or no change in total employment from AI, but 39% expect their employer to cut jobs because of it in the coming year, up from 32% in 2025. McKinsey adds that last year’s reductions “fell well short of what respondents in last year’s survey had anticipated.”¹

“Organizations’ conviction in AI is growing faster than the immediate financial returns they can attribute to it.”

Michael Chui, a co-author, argues the delay is normal: “It should not be surprising that it has taken time.” He puts the return the high performers do see down to changing the organisation, not to adding tools.¹ That is the useful part for a buyer, and Section 4 takes it up.

03Every 2026 survey finds the same thing: a minority with a return

McKinsey is not alone. PwC’s 2026 Global CEO Survey, of 4,454 chief executives in 95 countries, found 56% saying they have got “nothing out of” their AI investments so far, and 12% reporting that AI both grew revenue and cut costs. Deloitte’s 2026 State of AI in the Enterprise, which surveyed 3,235 leaders from director to C-suite, found 66% reporting productivity gains from AI and 20% reporting revenue growth.³ In India, a Nasscom-KPMG whitepaper of July 2026 puts the share of organisations reporting ROI across multiple AI use cases at 24%.⁴

The gap between how productive people feel and what shows up in the accounts appears in every one of these surveys. Deloitte has 66% for productivity against 20% for revenue; McKinsey has 80% against 37%.¹³ The likeliest reason is accounting, not technology. An hour saved by one employee is not profit until the firm either stops paying for that hour or uses it to sell more, and most deployments are not designed to do either.

04What the few do differently: redesign first, then measure in business terms

McKinsey’s November 2025 State of AI reached the same conclusion, as The Next Web summarised it: what set the high performers apart was “not better technology choices but better organisational practices”. They redesigned workflows, scaled faster, built AI into business processes, tracked KPIs for their AI solutions, and had senior leaders visibly committed to the work.³ A separate McKinsey report covered by the same outlet described most current AI as “tools that accelerate existing work” while they “largely preserve underlying workflows”.³

Indian industry bodies say much the same. The Nasscom-KPMG whitepaper argues that workflows and decision rights “must be redesigned from first principles, rather than simply automating broken processes to make them move faster”, and that the advantage goes to firms that reorganise, not to those running the most pilots.⁴ Nasscom’s June study of 505 enterprises in more than 12 regions found that its AI-first group mostly tracks AI value with the enterprise KPIs it already uses, on growth, monetisation, resilience and governance, rather than with new AI metrics.⁵

05Before you renew: six tests for an AI deployment

Most AI is bought as a subscription, so the moment to apply all this is the renewal. The seat price is the easy part. Microsoft 365 Copilot, for example, is listed on TechBag’s intel page at about US$30 a user a month as an add-on to an existing Microsoft 365 licence.⁷ Agents increasingly add usage-based charges on top, which is why one respondent in five already says operating costs constrain their use.¹

None of this needs a consultant. It needs the measure chosen before the tool goes live, which is the step most deployments skip. The older pattern of paying for software nobody uses is in our piece on where enterprise software ROI leaks, and what an AI seat costs a small firm is in our note on SMB AI seat prices.