Certainly, AI is increasingly demonstrating its capability to handle entry-level tasks at a significantly lower cost for companies compared to the expenses associated with hiring and training young professionals. According to a report by J.P. Morgan, corporations stand to save billions of dollars annually by reducing their workforce through automation. In fact, a 2025 study from Stanford University indicates that AI is already starting to significantly impact entry-level workers in the American labor market, with a 13 percent decline in employment among workers aged 22 to 25 in the most AI-exposed jobs.
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However, while replacing entry-level workers with AI may boost short-term profits, it could ultimately deplete the talent pool and create substantial vulnerabilities over the long term. By automating the "apprentice" phase of work—a crucial period where young workers learn from mistakes, receive mentorship, and develop sound business judgment—companies risk fostering a generation of knowledge workers who, although technically employed, are ill-prepared for leadership roles.
This issue extends beyond new graduates. Current managers may be reaping financial benefits by substituting technology for labor, but in doing so, they neglect to invest in the human resources essential for their companies' future success. This approach jeopardizes organizational sustainability and survival in the long run. Even if some firms that automate entry-level roles continue to thrive individually, the collective impact could lead to a significant national talent shortage, undermining the United States' competitiveness globally for decades.
Traditionally, business leaders have understood the importance of investing in new employees, recognizing that it takes time for them to become fully productive and contribute to the organization's success. They acknowledge that, regardless of a new employee's educational background, much of their learning occurs on the job.
Today, however, many companies are turning to AI and other technological advancements to fill roles once occupied by entry-level employees. While more experienced workers may effectively utilize these technologies to advance organizational goals, what happens when these individuals leave the company due to retirement or other reasons? The organization may be left with sophisticated technical systems but lack the expertise and judgment needed to apply and critically evaluate these systems.
Furthermore, the pool of well-trained, skilled individuals who would have gained expertise within a few years at the company may dwindle, especially as many senior managers, who are Baby Boomers, approach retirement. If companies replace too many junior professionals with technology and fail to provide sufficient opportunities for new "apprentices" to learn the business, they may soon struggle to find qualified senior leaders. Even more concerning, company culture—the vital organizational element that Peter Drucker famously said "eats strategy for breakfast"—may not survive without the necessary "muscle memory."
As Cornelia C. Walther, a visiting scholar at the University of Pennsylvania's Wharton School of Business and director of global alliance POZE, warns in Knowledge at Wharton: "Organizations face a perfect storm. Their most experienced professionals are leaving while the mechanism for creating new skilled workers has 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 consult with our Dean's AI Roundtable of seasoned executives from various industries. A key consensus among these participants is that business education must produce graduates who are not only technically proficient but also ethically grounded and adaptable. They also agree that companies should not overreact by drastically reducing entry-level training opportunities for future leaders.
These executives, along with others I've spoken with, view technological competency as essential, meaning AI fluency is as crucial for entry-level professionals today as Excel skills were a few years ago. However, they emphasize that the distinguishing characteristics of candidates are their ability to handle unexpected problems, balance competing interests, demonstrate sound judgment, think critically, and possess the emotional intelligence to work effectively in teams and build trust. These skills have always been and remain the key ingredients for successful business operations.
This is particularly relevant given that much of the nation's GDP comes from the service economy. While robots can provide many well-defined services, the ability to offer a personal touch—something only humans can provide—will set companies apart. Without relationally skilled individuals, U.S. businesses may fall behind other nations in the global market.
Businesses are not merely networks of technological tools; they are complex social systems. Managers must still depend on individuals to make things happen and strive for a balance between human and technological resources. Ultimately, they cannot overlook the human capital they will need in five years and beyond. In short, it is short-sighted to invest heavily in new technology while neglecting the people who make any organization truly exceptional. Entry-level tasks may be easily and cheaply replicated by AI, but entry-level employees do not remain at that level forever, and the knowledge they acquire in their first few years on the job is crucial for the organization's long-term success.