For months, the loudest voices in artificial intelligence—including OpenAI’s Sam Altman and Anthropic’s Dario Amodei—warned that entry-level white-collar jobs were headed for extinction. In recent weeks, both have walked back those statements.
And according to Cognizant CEO Ravi Kumar S., who oversees a workforce of more than 350,000 employees, the outcry wasn’t just a prediction gone wrong—it was fearmongering.
“There was a little bit of fearmongering from reading about the fact that there’s going to be a collapse of jobs,” Kumar said at Fortune’s COO Summit in Scottsdale, Arizona on Monday. “I think there will be more jobs.”
Cognizant hasn’t been immune to restructuring and layoffs as it works to transform for the AI era. But Kumar told Fortune’s executive editorial director Diane Brady that the company hired 20,000 entry-level college graduates last year alone—and expects that number to grow in 2026.
Some of those roles will likely fall under Cognizant’s new AI Builder strategy, which introduces two new positions: Frontier Certified Engineer and Frontier Business Operator. And even though his company is focused in the tech world, candidates don’t need a technical background to qualify.
“It could be a history major with skills to identify and use agentic work. It could be a biology major known as life sciences. It could be an HR accountant who can use agentic Claude terminals around them,” he said.
The workforce pyramid will begin to flatten, Kumar added, as there remains a need for both entry-level workers—as well as leaders to guide directions (he called the chief operations officer the most important role in any company). But in the middle, he said, is where AI will take charge.
“AIs will be in the middle of a flow. You want to have a ton of jobs in the front, you will have a ton of jobs in the back,” he said. “These are going to be validation and verification jobs, and those are going to be authentication jobs. Now, when you have a flat-earth pyramid, the biggest challenge is the middle layers are going to be leaner.”
As companies have raced to demonstrate AI productivity gains, many have turned to token consumption as their primary measuring stick. Meta, Amazon, and OpenAI are among those that have leaned on token metrics as an internal measure of productivity. Kumar thinks that’s the wrong approach.
“For the last two years, how you consumed tokens, how much tokens you consumed was a vanity metric,” he said. “…I don’t think you should equate this to the number of paid hours. I don’t think you should equate this to productivity.”
Instead, Kumar argued that knowing how and when to deploy tokenization strategically will become a discipline in its own right — one that individual teams will need to develop and refine based on their specific workflows and business goals.
“It has to be grounded in the company’s hustle,” he said in the Fortune conversation titled “Great Restructuring: Rethinking Talent Strategy in the Age of AI.”
The broader shift, in Kumar’s view, is away from measuring inputs entirely: “We have to go from delivering projects, delivering billable hours, owning outcomes, and finally we have to underwrite those outcomes and be paid for those outcomes. I think that is the future. I believe we are going to reforge, and whoever reforges this future is going to be a winner on the other side.”
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