Without question, AI increasingly has the ability to complete some entry-level tasks at far less cost to companies than the hiring and training of young professionals. A report by J.P. Morgan estimates that corporations can save billions of dollars a year by employing fewer people through automation. And, in fact, a 2025 study out of Stanford University has found that AI is already “beginning to have a significant and disproportionate impact on entry-level workers in the American labor market,” with workers between the ages of 22 and 25 in the most AI-exposed occupations experiencing a 13 percent decline in employment.
Yet while replacing entry-level workers with AI can boost profits in the short term, it will ultimately drain the talent pool and create real vulnerabilities over the long haul. By automating the “apprentice” stage of work—the time when young workers learn how to make low-cost mistakes, gain guidance from experienced mentors, and practice thoughtful business judgment—companies risk creating a lost generation of knowledge workers who are technically employed but unprepared to lead.
In the end, this won’t just be a problem for new graduates. Today’s generation of managers may be extracting gains from their businesses by substituting technology for labor costs, but by doing so, they are also failing to reinvest in the human resources that their companies need to thrive into the future. In the process, they may be risking their organizations’ sustainability and survival over the long haul. Most important, even though some firms that automate entry-level roles may continue to perform well individually, the collective impact could be a major national talent deficit, jeopardizing the United States at large for decades and damaging its competitive position worldwide.
Traditionally, business leaders have been willing to invest in hiring and onboarding new employees, recognizing that it will take some time for those workers to learn enough to be as productive as possible and fully contribute to the organization’s success. They’ve recognized that, however well-educated a new employee might be, that person will usually learn much more once they’re actually on the job.
Today, however, many companies are instead relying on AI and other technological advances to replace the roles that entry-level employees once played. And while many more-seasoned workers are becoming competent enough to apply such new technologies in ways that can advance an organization and its objectives, what will happen when that organization starts to lose those individuals as they move to other firms, retire, or depart for other reasons? It will be left with a variety of technical systems, but without the people who have the expertise or judgment to apply—and question—those systems effectively.
In fact, an entire tranche of well-trained, skilled, and knowledgeable individuals who previously would have gained such expertise within a few years at that company may very well not be there, especially given that many senior managers in companies today are Baby Boomers on the verge of retiring. If companies replace too many junior professionals with technology and do not provide a sufficiently large entry class of new “apprentices” opportunities to learn the business, they may soon find senior leaders increasingly hard to find. Worse, company culture—yes, the organizational element that Peter Drucker famously wrote “eats strategy for breakfast”—will not have the muscle memory to survive.
As Cornelia C. Walther, a visiting scholar at the University of Pennsylvania’s Wharton School of Business and director of global alliance POZE, has warned in the school’s journal, Knowledge at Wharton: “Organizations face a perfect storm. Their most experienced professionals are leaving while the mechanism for creating new skilled workers have been automated away. This creates what systems thinkers call a ‘delayed feedback problem’—the immediate efficiency gains mask longer-term consequences that won’t become apparent until knowledge gaps emerge during complex challenges.”
At the Kelley School of Business at Indiana University, we regularly engage with our Dean’s AI Roundtable of seasoned executives whose companies span a wide variety of important industries. A key consensus among the roundtable participants is that business education must produce graduates who are not only technically fluent but also ethically grounded and organizationally agile. They also broadly acknowledge that companies should not overreact by decimating the entry-level training ground for the next generation of company leaders.
They and other executives with whom I’ve spoken view technological competency as table stakes, meaning AI fluency is as essential to any entry professional as Excel skills were just a couple years ago. However, they all indicate that the separating characteristics that differentiate candidates are those such as the ability to deal with unexpected problems, to balance competing interests, to demonstrate good judgment and make sound decisions, to have critical-thinking skills, and to have the EQ to work well in teams and establish relationships of trust. Those have always been and still are the key ingredients to the secret sauce of how good business gets done.
That’s especially the case given how much of our nation’s GDP is made up of a service economy. Robots can certainly provide many highly defined services to customers, but what will distinguish companies from the pack is the ability to offer customers and clients the personal touch only people can provide. Indeed, without relationally skilled individuals, U.S. businesses may increasingly lag other nations in the global market.
Businesses are not just a network of technological tools; they are complex social systems. Managers must still rely on individuals to make things happen and seek a balance between human and technological resources. Ultimately, they can’t ignore considering the human capital that they’ll need to have in place in five years and beyond. Simply put, they should take a long-term planning perspective and recognize that it’s short-sighted to buy lots of shiny new technology and forget about the people who make any organization truly great. Entry-level tasks may be easily replicable and cheaper with AI—but entry-level employees don’t stay entry-level forever, and what they learn in those first few years on the job is vital to organizations’ long-term success.
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