Tim Walsh knows the metric that is quietly reshaping how corporate America thinks about its workforce. It isn’t revenue per employee, which has anchored headcount decisions for decades. It isn’t productivity. It’s something Walsh, the chair and CEO of KPMG U.S., calls labor cost margin—and understanding it reveals more about where AI is actually taking the economy than almost anything else being said out loud in boardrooms right now.
“For every one of my engagements,” Walsh told Fortune, the question is, “What is my mix of labor? What’s my mix of technology? And what’s the overall cost of delivering that engagement?”
He said he would expect the “labor cost in the mix” to go down and for his technology costs within that same engagement to go up. “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.”
That logic—lower labor cost per unit of work, more total volume, net growth—is the quiet calculus running beneath nearly every major AI investment decision in corporate America today. And according to the 2026 KPMG U.S. CEO Outlook Pulse Survey, released Tuesday, the pace at which executives are moving toward that model is accelerating far faster than the public debate and hype around AI jobs has accounted for. It’s “dizzying” to do business in a genuine economic boom, he added.
