Research: Why Some Junior Employees Work Well with AI—and Others Don’tSKIP TO CONTENT
Harvard Business Review LogoGenerative AI<br>Research: Why Some Junior Employees Work Well with AI—and Others Don’t
by Ashish Agarwal, Anitesh Barua, Anu Puvvada, Fangchen Song and Wen Wen
July 23, 2026
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Summary.<br>Organizations need to understand how individuals create value beyond the AI baseline in real organizational settings, particularly in higher-stakes professional work requiring judgment, domain...more<br>Leer en españolLer em português
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Entry-level employees are on the front lines of a rapid shift in knowledge work. These jobs used to be full of tasks that created an onramp into an industry and helped junior employees start building expertise. But now, many of these tasks are at risk of being delegated to AI-powered workflows, which are increasingly capable of handling analytical, information-intensive assignments. And as AI continues to improve, research has shown it is quickly resetting the baseline, with the standard for acceptable output rising as models improve.
Ashish Agarwal is a professor at the McCombs School of Business at The University of Texas at Austin. He serves as an associate editor at Management Science and a department editor at Decision Sciences. His research focuses on artificial intelligence, digital platforms, the Internet of Things, and digital advertising.
Anitesh Barua is the David Bruton Jr. Centennial Chair in Business at the McCombs School of Business, The University of Texas at Austin. His research focuses on AI and digital transformation, and has been published in leading journals including Management Science, MIS Quarterly, Information Systems Research, and Organization Science.
Anu Puvvada leads KPMG Studio, where she combines forward-looking research with venture-building to identify emerging opportunities and launch scalable services and technology-enabled businesses.
Fangchen Song is a Ph.D. candidate at the McCombs School of Business, The University of Texas at Austin. Her research examines the impact of AI on team collaboration, organizations, and the future of work. Her work has been accepted for publication in Information Systems Research.
Wen Wen Wen Wen is an associate professor at the McCombs School of Business at the University of Texas at Austin. She studies how AI and digital technologies are reshaping work, productivity, and organizational performance. Her research has been published in leading journals, including Management Science, Information Systems Research, MIS Quarterly, Strategic Management Journal, and Journal of Marketing Research.
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