AI adoption widens, but profit payoff lags, McKinsey survey finds
AI use is now widespread in business, but enterprise-level financial gains remain elusive, a new global survey shows.
Artificial intelligence has moved from the experimental phase to routine use in most companies, yet the technology's contribution to corporate profits remains stubbornly limited, according to a new global survey by McKinsey.
The 2026 survey found that nearly nine in ten respondents say their organizations regularly use AI in at least one business function. The share of companies scaling AI across the enterprise rose to 44 percent, up from 38 percent a year earlier. Adoption across three or more business functions also increased, reaching 56 percent from 51 percent.
Despite this broader deployment, the financial returns have not kept pace. Only 37 percent of respondents said AI had positively affected their earnings before interest and taxes, a figure that is broadly unchanged from 2025. A small group of just 6 percent qualified as AI "high performers," meaning they attributed at least 5 percent of EBIT to AI and described its impact as significant.
The gap between individual and corporate benefits is stark. Eighty percent of respondents said AI improved their own productivity, and half said it helped them make better decisions. McKinsey suggests the challenge for businesses is shifting from encouraging individual use to redesigning workflows so that these productivity gains translate into measurable financial outcomes.
The survey indicates that companies achieving the strongest returns are taking a different approach. High performers are more likely to focus on growth and innovation alongside efficiency. Nearly three-quarters of them have fundamentally redesigned workflows around AI, compared with only about a quarter of other respondents. They are also 3.3 times more likely to plan using AI to fundamentally transform their businesses over the next three years.
The findings suggest the next phase of AI adoption will be less about adding new tools and more about organizational change. Companies will need to redesign end-to-end workflows, measure financial impact, manage AI-related costs, and secure senior leadership commitment to turn rising AI investment into sustained returns.