Cognizant is ramping up entry-level hiring as artificial intelligence reshapes the workforce, with CEO Ravi Kumar S telling Fortune the company is bringing on more school graduates this year than ever before—and he’s looking beyond traditional tech majors to liberal arts colleges and community colleges.Kumar’s unconventional hiring strategy stems from his belief that AI will widen the base of corporate employment rather than shrink it. “I can take a school graduate and give them the tooling so they can actually punch above their weight,” he told Fortune. “AI is an amplifier of human potential. It’s not a displacement strategy.”
Liberal arts graduates find new tech opportunities
The CEO of the 350,000-employee IT consulting firm is actively recruiting non-STEM graduates, including anthropologists, sociologists, psychologists, and journalists. His rationale: as expertise becomes accessible at everyone’s fingertips through AI, specialisation loses its premium. “Intelligence is not the asymmetry. Applying intelligence is the asymmetry,” Kumar explained.He urged students to “start to focus on interdisciplinary skills,” citing examples like historians blending computational skills to become futurists or biology majors using AI to crack drug development cycles. According to Kumar, the corporate pyramid is becoming “broader and shorter,” with faster paths to expertise for those who can leverage AI tools effectively.
From STEM-focused to problem-finding roles, Cognizant’s approach to hiring graduates
Kumar sees AI handling the “middle” work—the execution and problem-solving—while humans focus on the beginning (prompting, conceptualising, finding purposeful problems) and the end (validation and verification). This shift means companies need more “problem finders” rather than just problem solvers, opening doors for disciplines traditionally outside tech’s core.The shift extends beyond hiring. Cognizant has launched apprenticeship programs in 30 states and partnered with Merit America for mid-career shifts, offering a “work, earn and learn” model. Kumar acknowledges a critical caveat: AI’s benefits must be “distributed equitably” rather than concentrated among a few to truly boost productivity and create wage distribution.“As people are living longer, the life of their skills is getting shorter,” Kumar noted, emphasising that future workers will need multiple careers in one lifetime—making adaptable, interdisciplinary skills more valuable than narrow expertise.
