Starting a career when AI is changing the rules

For today’s graduates, starting a career is becoming more challenging as the world of work rapidly changes. The numbers behind this year's graduating classes make for uncomfortable reading. Entry-level job postings have fallen roughly 35 percent since early 2023, according to Revelio Labs data, with some tech and data roles down by as much as two-thirds. Nearly 43 percent of college graduates aged 22 to 27 were underemployed as of late 2025, the highest rate since the pandemic. Goldman Sachs has found that employment among 22-to-25-year-olds in AI-exposed roles fell 16 percent between late 2022 and mid-2025, even as employment for more experienced workers in the same fields held steady. Anthropic CEO Dario Amodei has gone further, predicting AI could eliminate roughly half of all entry-level white-collar positions within five years.

Against that backdrop, it is little wonder that young people entering the workforce are anxious. But Arun Sundararajan, the Harold Price Professor of Entrepreneurship at NYU's Stern School of Business, believes the anxiety, while understandable, shouldn't be the whole story. Speaking with the World Economic Forum's Robin Pomeroy and CGTN's Xin Guan on the Radio Davos podcast, Sundararajan, a longtime advisor to the WEF's AI Governance Alliance, laid out how he counsels his own students to navigate a labor market with no predictable script left to follow.

Build your portfolio while the barriers are low

Sundararajan's central piece of advice starts from a reframing of the moment students are living through. "If the barriers to creating things of value have been lowered, go out and start to create them while you're a student," he said. That guidance does double duty, in his view. It gives young people a demonstrable body of work, proof of what they're capable of, while also preparing them for a possibility he takes seriously, that traditional employment may not be the default structure of work going forward. Just as importantly, he argued, the habit itself has lasting value. "It also sort of builds that muscle that allows you to be flexible and resilient and adaptable," noting that developing that capacity between the ages of eighteen and twenty-two will "serve you in the long run" regardless of how the job market evolves.

Sundararajan pushes back on the more apocalyptic framing of AI's effect on hiring. "It's not like companies will not want any humans," he said. What's shifting, in his assessment, is which humans get hired. "In the short run, they may need fewer entry-level humans, but the ones that they need are going to be the ones who know how to dramatically increase their output using AI, and there will actually be a premium on that kind of human."

That framing lines up with what labor-market data is showing. Rather than outright job destruction, researchers have increasingly described a "seniority tilt": entry-level postings narrowing and shifting in composition, while experienced workers who can direct AI tools effectively remain in demand. SignalFire data shows new graduates made up just 7 percent of big tech hires in 2024, down more than 50 percent from 2019.

Networking matters more

If AI is compressing the traditional entry point into careers, Sundararajan argues human relationships become correspondingly more valuable, not less. "Networking has never been more important," he said. "A big part of your value in the future is going to be your set of connections, and so invest in that very heavily." He pointed to a specific window of opportunity that closes the moment students graduate. "There's never a better time to do that when you're a student, because you can always go up to someone and say, 'I'm a student. I'd like to learn from you.' Once you're no longer a student, that doesn't work as well."

Perhaps Sundararajan's most striking advice is a warning against false certainty, including his own. "Anyone who tells you they know exactly what kinds of work AI is displacing and what's going to happen in the long run, I would not take too seriously," he said. He's candid about what makes this moment harder than the one previous generations faced. "Compared to people who were in their position ten years ago, there isn't a predictable path to starting their careers," he said. "It's something they're going to have to make up as they go along, so it's going to take a lot more resilience and adaptability."

Crucially, he framed the outcome as unresolved rather than predetermined. "Whether this generation is left behind by AI will depend in part on how it responds," he said, placing real agency back in the hands of the students he's advising, even amid a labor market that offers them fewer guarantees than any graduating class in recent memory.

The statistics paint a genuinely difficult picture for today's graduates, narrower entry points, declining junior hiring, and a job market reshaping itself faster than institutions can track. But Sundararajan's advice suggested the response isn't paralysis. Build a portfolio. Invest in relationships while the asking is still easy. Learn to multiply your output with AI rather than compete against it. None of that guarantees a smooth start. But for a generation facing a future no one can fully forecast, it may be the closest thing to a map currently available.