AI is helping workers get more done, though not necessarily delivering broad benefits for the organizations that employ them, according to a top McKinsey & Company executive.
Eric Kutcher, a senior partner and chair of McKinsey North America, told reporters at the company’s media day on Wednesday that outside specific areas such as software development, many of the hoped-for productivity increases have yet to materialize across companies.
“You have people that are getting more productive as individuals, but they’re just changing some of the work that they’re doing,” he said.
Until companies look at the scope of work across an organization and identify inefficiencies in the system, it’s hard to generate sweeping increases in output, Kutcher said.
“We have not gotten enterprise-level productivity, with the exception of a few areas,” he said.
Early on, he said, many companies’ attempts to supercharge workers’ productivity meant giving them access to tools like Anthropic’s Claude and OpenAI’s ChatGPT and, in some cases, telling them to use them as much as possible.
Kutcher said that some companies even ranked who was using the most AI tokens “without realizing those tokens cost money.”
That gap between workers’ and companies’ results shows up in McKinsey data. In August, the consulting firm’s AI division, called QuantumBlack, reported that in a survey, eight in 10 respondents said AI had increased their productivity.
At the same time, the survey found that the share of respondents who said that AI had contributed to their organization’s profits from core operations — before interest and taxes — was essentially flat from a year earlier, at 37%.
Kutcher said the technology’s benefits have materialized in areas such as software, where developers have used AI to generate more code. That can translate, he said, into quicker releases of new products and features.
More businesses appear to be trying to turn the productivity boost software developers have seen from AI into broader results. McKinsey’s survey showed a six percentage-point increase from 2025 to 2026 in the share of organizations using AI that were moving beyond experimentation and pilot phases into “scaling” mode.
Many organizations, Kutcher said, “are trying to figure out right now, ‘How do I shift from this individual productivity into the institutional?'”
To make that shift, Kutcher said, some companies are rethinking a key part of their business, from end to end. For a life-sciences company, that might mean considering how AI could remake research and development; for an oil-and-gas company, it might mean new approaches to drilling.
“You pick the area and say, ‘How would I do this profoundly differently?'” he said.
