As artificial intelligence reshapes the entry-level job, we can no longer rely on the traditional apprenticeship model to develop future leaders.
Twenty-five years ago, if you dreamed of one day becoming a CEO, your early jobs consisted of work you probably didn’t particularly enjoy: building spreadsheets, poring over legal cases, combing through research, staying late to create presentations. It was repetitive and often tedious work, but it was also formative; the opportunity many future leaders needed to learn the fundamentals of business.
Today, artificial intelligence (AI) can complete much of that foundational work in a matter of minutes – a huge efficiency gain for chief executives across industries, to be sure. But it also raises an important question: If AI removes the work that once taught judgment, resilience and business instincts, where will tomorrow’s leaders learn those skills?
The World Economic Forum reports that 40% of employers expect to reduce their workforce where AI can automate tasks, while Stanford researchers have found employment among 22- to 25-year-olds in AI-exposed occupations has declined significantly since generative AI entered the workplace. At the same time, unemployment among recent college graduates has climbed to 5.6%, underscoring the uncertainty facing those beginning their careers.
The question today’s leaders must grapple with isn’t simply what happens to entry-level jobs. It’s what happens to an organization’s leadership pipeline when the first rung of the career ladder is being rewritten.
Future leaders can’t afford to learn passively
YPO member Peggy Choi knows firsthand the value of the traditional apprenticeship model. Before founding tokenization company Craftt and enterprise AI deployment company Anthora.AI, she spent years at Goldman Sachs and Silver Lake, experiences she credits with building the skills that shaped her career. Today, she believes AI is forcing the next generation to develop those same qualities far more intentionally.
“It’s no longer an option to passively learn on the job,” she says. “You have got to be very proactive in developing yourself from the start.”
So how do entry-level employees build up that industry and institutional knowledge without the years of the hands-on “grunt” work of the past?
“I do worry a lot,” admits Choi. “If you haven’t done the work, it’s almost impossible to know what to look for.”
She doesn’t have a clear answer, but until organizations rethink how they develop early-career talent, she believes much of the responsibility falls on individuals. Rather than absorbing judgment through repetition, future leaders must actively seek it — learning not only how to use AI, but how to question it. That means understanding where the technology excels, where it falls short, and when human judgment should take precedence.
— Peggy Choi, Founder, Craftt share
And the work itself is already beginning to evolve. Rather than spending their early careers completing every task manually, Choi believes young professionals will increasingly be expected to improve the systems doing the work.
“We need our employees to start to train the models,” she says. “A big part of our work becomes training and benchmarking and evaluating.”
In many ways, she says, learning to manage AI isn’t all that different from learning to manage people. Both require clear direction, evaluating performance and knowing when to intervene. The technology might do the work, but humans will remain responsible for improving it and, above all, applying good judgment.
Organizations must build intentionally
“There is a risk that we are creating a huge leadership gap right now,” warns YPO member Gregor Fiabane on the impact of AI on entry-level jobs.
As Managing Partner at Korn Ferry, Fiabane has spent his career helping organizations identify, develop and succession-plan future leaders. From his perspective, the challenge is making sure organizations replace what is being removed.
“Organizations must intentionally redesign their development models,” he says. “The traditional apprentice model may no longer happen, but leadership development remains deeply human.”
Fiabane believes companies can no longer assume leadership capability will naturally emerge over time. Instead, organizations must create the experiences that repetitive work once provided. That doesn’t mean recreating busywork. Rather, it’s all about giving early-career professionals the opportunities to develop judgment through mentorship, coaching, rotational experiences, stretch assignments and leadership exposure — all things AI can’t automate.
Ironically, this makes AI more of an opportunity than a challenge in his eyes: By eliminating administrative tasks, organizations can now expose young professionals to more strategic work earlier in their careers.
— Gregor Fiabane, Managing Partner, Korn Ferry share
“AI may really accelerate the learning,” he points out. Yet he doesn’t believe the qualities that define great CEOs are changing nearly as much as the path to becoming one.
“Critical thinking is becoming much more important,” he says, adding that vision, strategy, judgment and the ability to rally people around a common purpose are leadership fundamentals that will remain consistent.
Choi believes that if organizations and future leaders embrace the challenge, AI has the potential to return leadership to its most human work. By automating more of the operational execution, leaders may ultimately have more time to focus on judgment, relationships, culture and developing people. “We’ll have a lot more time to really be in touch with the core,” she says. “We’ll think a lot more about humans, what we enjoy doing and how we create those experiences.”
