KPMG CEO Says Labor Cost Margins Are the Key Metric for Measuring AI Impact

Tim Walsh, chair and CEO of KPMG U.S., has a single question he runs through every client engagement: what is the mix of labor versus technology, and what does the total cost of delivery look like? That ratio, which he calls labor cost margin, is the metric he says reveals more about AI's true economic impact than almost anything else discussed in corporate boardrooms today.

"For every one of my engagements," Walsh told Fortune, "what is my mix of labor? What's my mix of technology? And what's the overall cost of delivering that engagement?"

The metric is deliberately distinct from the figures that have traditionally driven headcount decisions. It is not revenue per employee, which has anchored workforce planning for decades, and it is not productivity in the conventional sense. Labor cost margin, as Walsh describes it, captures the substitution of technology for labor, the expansion of capacity without proportional headcount growth, and the productivity gains that every CEO is now under pressure to deliver.

Walsh expects the labor cost component of that mix to fall as AI adoption deepens, while technology costs within the same engagement rise. The payoff, in his framing: scale. "And at the end of the day, I'm going to be able to run a lot more volume through my business in ways that I couldn't before." Lower labor cost per unit of work, more total volume, net growth. That calculus, he argues, is the quiet logic driving the majority of major AI investment decisions in corporate America right now.

The pressure to move is not abstract. "It's stressful if you're not investing, if you're not keeping up," Walsh said. "Because if you're not keeping up, you have the risk of losing market share."

The 2026 KPMG U.S. CEO Outlook Pulse Survey, released Tuesday, puts hard numbers behind that anxiety. The survey of 100 chief executives of large American companies found that 77% agreed generative AI was overhyped over the past year, but also that its true disruptive potential over the next five to ten years is likely to be under-hyped. The pace at which executives are shifting toward the labor-cost-mix model is accelerating faster than the public debate around AI jobs has accounted for, according to the survey findings.

Walsh acknowledges the environment itself is disorienting. It is "dizzying," he said, to do business in a genuine economic boom.

On the workforce side, Walsh asserts that disruption will reach every level of the organization, though he stops short of predicting specific outcomes. Corporate leaders more broadly are describing the transformation in work processes and task allocation between humans and technology as significant but initially gradual, a contrast to the more extreme narratives dominating public discourse on AI and jobs.

For KPMG employees and clients alike, the practical implication of Walsh's framework is straightforward: the question is no longer whether AI will change the cost structure of professional services work, but how quickly the labor-to-technology ratio shifts, and whether firms are moving fast enough to stay competitive in the process.