Cognizant and Pearson have published research suggesting that entry-level roles are being redesigned by artificial intelligence rather than disappearing outright.
The joint AI Workforce Pulse study found that 94% of HR leaders expect AI to create new entry-level roles within the next five years, while 96% expect entry-level jobs to evolve into positions where employees supervise or manage AI systems.
The research also points to a growing training gap. Ninety-one per cent of respondents said employee requests for AI training had increased over the past year, yet 46% of organisations are not proactively arranging AI training. Sixty per cent said their company’s learning and development programmes cannot keep pace with the speed at which AI is transforming jobs.
The study was based on a Wakefield Research survey of 750 HR professionals at director level and above, across companies with at least 1,000 employees in the United States, United Kingdom, and India. The fieldwork took place between 23 March and 3 April 2026.
The findings challenge the assumption that AI will simply remove early-career work. Instead, the research suggests the first rung of the career ladder is changing in content, skills, and supervision. Routine execution is giving way to oversight, judgement, problem-solving, and collaboration with AI systems.
Kathy Diaz, chief people officer at Cognizant, said: “AI is reshaping the talent landscape and exposing the limits of traditional talent and learning models. With the fundamental shift in entry-level tasks and skill requirements changing rapidly, organisations must rethink how they hire and develop talent at pace.”
The study found that 69% of HR leaders believe broad, interdisciplinary backgrounds are more important for early-career talent than deep specialist skills or focused degrees. Two-thirds said they value liberal arts degrees more than they used to because of AI advances, while 97% said soft skills matter more than ever.
Ali Bebo, chief human resources officer at Pearson, said: “As work evolves, the most successful organisations will focus less on replacing tasks and more on building the capabilities that help humans and AI work together. That starts with early-career talent.”
She added: “The future belongs to organisations that combine AI innovation with a deep understanding of how people learn, develop, and apply new skills in the real world.”
The findings build on Cognizant’s earlier New Work, New World 2026 study, which found that AI is already affecting 93% of jobs. Cognizant said it hired 20,000 fresh graduates in 2025 and expects to exceed that number in 2026.
The research lands amid intense debate over whether AI will hollow out graduate and entry-level employment. Early-career roles have traditionally given new workers exposure to basic tasks, organisational context, client work, internal systems, and professional judgement. If AI automates too much of that foundational work, employers risk weakening the future management and specialist pipeline.
Concerns over uneven AI confidence and training were explored in AI readiness gap widens at work. The Cognizant and Pearson findings extend that challenge into hiring, early-career development, and job architecture.
The emerging model is not only about teaching employees to prompt tools. Entry-level employees may need to understand how AI outputs are generated, where errors appear, how to check work, when to escalate, and how to apply human judgement in workflows that are partly automated. That requires structured learning, not informal trial and error.
Middle managers also become more important. The study found that more than 90% of respondents believe middle managers are instrumental to redefining job roles as AI changes day-to-day work. That places managers in the middle of role design, productivity expectations, training, performance measurement, and employee confidence.
Hiring filters may need to change. Employers that previously screened for narrow technical credentials may place more weight on adaptability, communication, systems thinking, ethics, domain curiosity, and the ability to work across disciplines. Technical skills still matter, but they may not be enough where AI changes the nature of execution.
Learning and development teams face a harder test. AI literacy needs to be built into onboarding, graduate schemes, apprenticeships, manager training, compliance, and career progression. Organisations that leave early-career employees to learn informally may create uneven capability, inconsistent quality, and avoidable risk.
Entry-level work remains essential because it builds the future workforce. Employers now face a choice between redesigning it deliberately or allowing AI adoption to erode the training ground on which future specialists and leaders depend.
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