Survey: AI Boosts Productivity, but Few Firms See Profit Impact

Individual gains, limited enterprise impact

McKinsey & Company's 2026 survey on the state of AI, published in August 2026, found that 80% of respondents said AI has improved their individual productivity, and 50% said it helps them make better decisions. Despite this, only 37% of respondents said AI has contributed to their organization's earnings before interest and taxes (EBIT), a figure McKinsey says is essentially unchanged from the prior year's survey. McKinsey also reported that its share of AI high performers, defined as organizations attributing at least 5% of EBIT to AI with significant reported impact, has remained flat at about 6% of respondents.

Deloitte's State of AI in the Enterprise 2026 report, part of its ongoing research series from the Deloitte AI Institute, found a similar pattern in how companies are applying AI internally. Deloitte reported that 37% of surveyed organizations are using AI at a surface level with little change to existing processes, 30% are redesigning key processes around AI, and 34% are using AI to deeply transform products, services, or business models. Deloitte's methodology involved surveying 3,235 leaders across 24 countries between August and September 2025.

Costs, governance, and procurement shifts

McKinsey reported that about 20% of respondents said AI-related operating costs, including token costs, have constrained their organization's AI use, even though 60% of respondents said they expect to increase AI investment over the next year. McKinsey also found that 32% of respondents said their organizations had decided against purchasing at least one software product or feature because it could be built internally using agentic coding tools, a pattern most commonly reported by respondents in technology and healthcare.

On scaling of AI agents, McKinsey found that 40% of respondents from organizations with more than $1 billion in annual revenue reported scaling AI agents in at least one function, up from 27% a year earlier, while the share at smaller organizations remained flat at 22%.

Deloitte's report separately found that 42% of surveyed organizations view their AI strategy as highly prepared, while preparedness ratings were lower for infrastructure, data management, risk and governance, and talent. Deloitte also reported that only about one in five organizations has a mature governance model for autonomous AI agents. On workforce response, Deloitte found that education aimed at raising general AI fluency, cited by 53% of respondents, was the most common talent strategy adjustment, ahead of measures such as redesigning roles or career paths.

What the gap may mean for planning

MarketScale analysis: The divergence between individual-level productivity gains and enterprise-level financial impact, as reported in both surveys, suggests that many organizations have deployed AI tools without redesigning the workflows, metrics, or governance structures those tools operate within. Companies evaluating further AI investment may want to review how AI-related costs are tracked, how existing software renewal decisions account for internally built alternatives, and whether governance structures exist for any AI agents already in use, before expanding deployment further.