By Murugan Anandarajan, Professor of Decision Sciences and Management Information Systems, Drexel University, and Stacy Kline, Learning Clinical Professor of Accounting, Drexel University
Artificial intelligence has become part of routine business operations, as employers across most industries use AI for tasks ranging from drafting reports to analyzing data. We are business professors at Drexel University who have spent the past year examining how AI is changing both the workplace and the classroom.
Much of the conversation in business education to date has centered on helping students learn how to use AI responsibly and effectively. Even so, our recent findings show that other qualities and skills still matter — especially as entry-level work itself is being reshaped by automation.
For many decades, entry-level positions have helped employers meet immediate business needs, while also giving new graduates a chance to learn from experienced colleagues through everyday work. Through this work, graduates learned how organizations operated and how experienced colleagues made decisions. Entry-level work, then, traditionally functioned as a kind of apprenticeship. Each assignment prepared graduates for more complex responsibilities.
But today a newly hired financial analyst may first review an AI-generated forecast or scenario analysis, rather than building the initial model from scratch. And a recent college graduate at a marketing firm may begin their new job by evaluating campaign ideas generated by AI, as opposed to drafting them from a blank page.
Many schools are incorporating AI into their curricula in different ways. Yet students are often still prepared for traditional, entry-level roles in which they develop judgment gradually — not the AI-mediated roles many will actually enter.
We spoke with 647 employers over the past year about workplace preparedness, as part of Drexel’s 2026 Early-Career Skills Outlook survey. Employers we spoke with consistently ranked communication, professionalism, teamwork, reliability and sound judgment above technical AI proficiency. AI skills also mattered, but these alone did not distinguish the strongest candidates.
The findings point to a continuing demand for the human capabilities that support professional judgment. The problem is that routine entry-level work has long helped graduates develop those capabilities. As more of that work is automated, new professionals may have fewer opportunities to practice communication, collaboration and decision-making on the job.
Employers cannot address this challenge alone. Business schools have traditionally provided the foundation for these skills. Our own school, Drexel University’s LeBow College of Business, reflects this broader trend by integrating AI into its programs while still emphasizing judgment-driven coursework.
The challenge is no longer simply to teach students how to use AI. It is to prepare them for workplaces where AI does much of the routine work, and where the value of a new hire lies in knowing when to question, refine or override what the AI produces.
This article is republished from The Conversation under a Creative Commons license. Read the original article.
