Early Careerist: The AI On-Ramp

For decades, a student’s first job out of college wasn’t meant to be glamorous. Entry-level analysts reconciled spreadsheets, coordinators assembled reports, and assistants proofed drafts. The work was often tedious, but it mattered. It was how young professionals learned.

Those early roles provided hands-on experience—translating classroom theory into workplace reality. In these positions, new professionals were supported by managers and mentors who explained not just what to do, but why it’s done.

In other words, early career roles functioned as on-ramps: a gradual merge into the fast-moving world of work. They gave new hires time to accelerate before joining the traffic of strategic decisions. But those ramps are narrowing—and in some cases, disappearing. Now, graduates are either left with no entry point or forced to swerve directly onto the highway at full speed.

It’s tempting to blame a sluggish economy. But that explanation ignores the compounding factors facing new graduates today. What’s happening is structural: the tasks that once defined early career work are no longer waiting for new hires. They’re waiting for AI.

A Changing Starting Line

Early career roles once offered a safe stretch of road—smaller, lower-stakes tasks that built confidence before larger responsibilities followed. In those early miles, new hires learned to navigate organizational dynamics, master basic processes, and build fluency in the rhythms of daily work. They would develop subtler skills too (think reading the room, managing relationships, finding their voice). This kind of supervised practice equipped them to take on greater responsibilities and make more complex decisions.

That early-stage work is starting to vanish. In fact, Korn Ferry’s AI Impact Score, based on our Success Profiles database, shows that in cognitive, computer-based work, lower-level roles are more exposed to AI than higher-level ones. The tasks that once helped young professionals gain experience are increasingly being automated—handled by AI with limited human oversight. And when that work is removed from entry-level jobs, the learning opportunities go with it. New hires now have fewer chances to prepare for the demands that follow.

Meanwhile, the starting point itself has shifted. While companies aren’t handing out mid-level titles, many “entry-level” roles now expect at least two years of experience. As a result, recent graduates face steeper expectations. Even in today’s tight labor market, underemployment remains widespread: a 2024 report from the Strada Institute and Burning Glass Institute found that, one year after graduation, 52% of college graduates were working in jobs that didn’t require a degree. It’s not about capability—it’s about a narrowing pipeline. And that narrowing has real consequences.

The new “entry-level” doesn’t look much like entry at all. Instead of beginning with the basics, new recruits are asked to start further up the ladder, where expectations are higher and the margin of error is smaller. Leaders are taking notice. Some tech leaders predict that up to half of entry-level office jobs could disappear soon as AI tools absorb routine cognitive tasks. A possibility, not certainty, but still, it underscores the risk: if the traditional starting point collapses without being rebuilt, we not only lose jobs but also the runway where people learn how to work.

The Fat Pyramid (If We Build It)

If the foundation of entry-level work is eroding, what replaces it?

Traditionally, the workforce was shaped like a pyramid: a broad base of junior, fewer managers in the middle, and a narrow band of leaders at the top. That structure worked because the lower levels handled the routine work while gaining experience. Now, as that foundation crumbles, organizations face a choice: allow the pyramid to hollow out or reimagine it—with the help of AI.

As automation takes over tasks, the foundation of entry-level work shrinks. But instead of eliminating junior roles, some companies are expanding their scope. With AI handling the basics like scheduling and data entry, early-career professionals can step into more strategic, high-impact work sooner (think analyzing data or advising teams). The result? A pyramid with a broader bed—or what Korn Ferry’s David Farris calls a “fat pyramid.”

In other words, entry-level jobs are evolving, and this change can energize ambitious hires. But it also carries risk. Without proper support, organizations may set new talent up to stumble. The “fat pyramid” only works if early-career professionals are equipped to meet the demands of their expanded roles.

It’s not a guarantee—it’s a choice. Companies can use AI to replace entry-level roles, reducing access or limiting learning. Or they can expand what junior roles can do, enabling new hires to contribute more meaningfully from the start. The difference lies in whether leaders are willing to redesign how people learn to do the work.

The New Early Career Skillset

If early career roles are broadening, then the definition of “job-ready” will need to shift, too.

As early careerists become close collaborators with AI, they will need to show sharper judgement and discernment—knowing when AI output is right, when it’s wrong, and when it’s irrelevant. What’s more, rapid technological development demands a more adaptable workforce. New hires can’t just memorize processes; they need the agility to learn, unlearn, and relearn as workflows change.

Of course, these qualities aren’t new. Organizations have always valued judgment, adaptability, and relationship-building. In fact, Korn Ferry research identifies learning agility as a top predictor of leadership potential. That competency holds greater relevance in an AI-enabled workplace, where tools evolve faster than processes can keep up. Our AI-Ready Leader Success Profile goes further, naming “championing learning and unlearning” as a core responsibility for leaders.

But where new employees once developed these skills after a year on the job, some companies expect them to have these capabilities from the first day on the job.

Why This Matters Now

The signals are clear: graduates are waiting longer for offers, underemployment is high, and entry-level roles are shrinking—especially in tech. At the same time, AI is reshaping the very roles that once taught judgment, adaptability, and workplace fluency. It’s not just changing how work gets done, but how people learn to work.

That shift leaves leaders with a choice. AI can compress opportunity, narrowing access to degree-matched careers and weakening talent pipelines that organizations claim they want to broaden. Or it can expand opportunity, creating a “fat pyramid” where junior employees contribute at a higher level earlier—provided they have the right scaffolding to succeed.

The outcome isn’t inevitable. It depends on how organizations design the first steps into work. When integrated strategically, AI can accelerate careers, widen access, and surface talent that might otherwise be overlooked. Done poorly, companies risk creating a generation of professionals who never had the chance to build the foundational skills leadership requires.

The on-ramp into a career won’t rebuild itself. Leaders will need to decide whether AI becomes a barrier or a bridge.