AI vs. Entry-Level Jobs: The Surprising Truth About Hiring Trends in 2024

A prevailing narrative suggests that AI is reshaping entry-level roles so rapidly that it's significantly altering hiring numbers for early-career talent. Many believe the end of entry-level jobs is near.

There's no denying that AI automates routine, repeatable tasks that have historically formed foundational skills for many early career roles (e.g., junior analysts, paralegals, basic coding roles, customer service representatives). But is the perception of radically reduced opportunity for early career talent actually reality?

Have organizations actually decreased the number of junior employees hired in the past 24 months? And if so, is a slowdown in hiring solely because of AI?

These are questions the Institute for Corporate Productivity (i4cp) explored in a recent pulse survey on current and future practices related to early-career talent, defined as recent graduates or professionals with zero-to-three years of experience in the workforce.

The survey gathered insights from 184 HR professionals, 125 of whom represented larger organizations (those employing more than 1,000 people) across industries including healthcare, financial services, manufacturing, technology, insurance, and consumer products.

Early Career Hiring is Holding Steady

What we found is that over the past two years, employers have generally maintained early-career hiring, with most expecting stable or increased hiring in 2026.

Most (43%) of the survey respondents from larger companies reported that the volume of hiring of early career talent in their organizations has remained the same in the past two years. A combined 34% reported that hiring of this cohort has increased somewhat or significantly during this period.

But while hiring of early-career talent may not be down in those organizations, many narrative survey responses made it clear that the bar is higher for entry-level talent than it has been in the past. Some noted they are raising skill requirements for entry-level positions and the expectation of so-called "day-one productivity" is very real.

We asked the combined 23% who reported that hiring of early career talent in their organizations has decreased somewhat or significantly in the past 24 months to expand on the reasons for those decreases. The responses to this follow-up question may be surprising—or maybe not.

It's Not AI—It's Economic Uncertainty

While there's no argument that AI may be a contributing influence on economic uncertainty, the number-one factor cited by those who said hiring of early career talent has decreased in their organizations was cost pressures (reductions in force, overall cost-cutting, higher interest rates affecting corporate growth, etc.), followed by overall economic uncertainty, organizational restructuring or shift in strategy, and anticipated future automation of early-career work.

And what about the payoffs versus risks? Will organizations look back with regret after holding off hiring humans in anticipation of fewer future needs as they operationalize AI? If their gamble doesn't pay off, will they have to scramble to cover skills gaps and absorb higher external hiring costs later? Will their leadership pipelines be hollowed out in the coming few years? Possibly. Only time will tell. Some are definitely rolling the dice, while others are taking a more pragmatic approach.

The Early Career Hiring Outlook for 2026 is Optimistic

Most survey respondents (50%) said they anticipate early-career hiring to remain steady in their organizations or even increase somewhat (22%) in 2026 with fewer (19%) expecting reductions.

Part of this optimism may be recognition that the recruitment and retention of early career talent is more important than ever in ensuring that mid-level pipelines don't become any more diminished than they already are in some organizations. A few survey participants noted that alarm bells are not ringing as loudly as they should be in their companies about the long-term impact on future leadership pipelines if early talent is not properly engaged and developed.

Others framed the current state of early-career opportunity as shifting, rather than vanishing. They are redesigning early career roles rather than eliminating them, embedding AI into internships and apprenticeships, and using AI to enhance and support early-career talent rather than replace the roles.

The question employers should be asking themselves now is: How do we redesign early career talent models in an AI-enabled workplace?