Cognizant Bets Entry-Level Jobs Will Grow Despite AI Automation
Cognizant CEO Ravi Kumar S. contradicted warnings that artificial intelligence would eliminate entry-level white-collar positions, saying fears of mass job losses were overstated. Speaking at Fortune's COO Summit in Scottsdale, Arizona, he outlined a hiring strategy that treats AI as a tool that reshapes rather than replaces the workforce.
The company, which employs more than 350,000 people, hired 20,000 entry-level graduates last year and expects to increase that number in 2026. Kumar introduced new roles - Frontier Certified Engineer and Frontier Business Operator - that deliberately don't require technical backgrounds.
A history major, biology graduate, or HR accountant can qualify if they can work with agentic AI tools like Claude terminals, Kumar said. The company's strategy assumes candidates need skills to identify and use AI agents rather than traditional programming knowledge.
The Flattened Pyramid
Kumar described AI as occupying the middle layers of organizational workflows, handling validation, verification, and authentication tasks. Entry-level workers and senior leaders will remain essential, but the middle tiers - traditionally filled with managers and analysts - will shrink.
"You want to have a ton of jobs in the front, you will have a ton of jobs in the back," he said. "AIs will be in the middle of a flow."
This structure differs from the traditional pyramid where the middle layers are thickest. Instead, Cognizant expects organizations to be leaner in the middle while maintaining robust entry and leadership levels.
Measuring Productivity by Outcomes, Not Inputs
Kumar also criticized how the industry measures AI productivity. Companies track token consumption - the volume of data processed - as a efficiency metric, but he called this approach a "vanity metric" that misses what actually matters.
He argued for measuring productivity by outcomes instead. "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," Kumar said.
This shift moves compensation models from time-based billing to results-based pricing, a change that would require both companies and clients to rethink how AI work is valued.
For executives planning workforce strategy, understanding how AI Agents & Automation reshape organizational layers is essential. Kumar's framework suggests that middle management roles face pressure while entry and senior positions remain stable - a dynamic that requires deliberate planning. Learn more about AI for Executives & Strategy to understand these structural shifts.
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