The conversation about AI and entry-level jobs usually stops at a headcount question: will there be fewer of them? This week, two of the most senior voices in global economics pointed at something more specific. The first rung of the career ladder is getting harder to reach.

That is not only a labor market problem. It is a design problem inside every organization that has ever said, “Start here, learn the work, and grow with us.”

If the routine work that used to teach people the job is moving to AI, then the job that taught people the work has quietly changed. Someone has to redesign it on purpose.

Key takeaways

  • At the IMF and World Bank annual meetings in Bangkok, IMF Managing Director Kristalina Georgieva said young people entering the labor market are the people to worry about first as AI spreads.
  • Singapore President Tharman Shanmugaratnam said the first job after graduation is now seeing less demand, and that AI displacement is happening task by task.
  • Entry-level roles were never just a set of tasks. They were a bundle of routine work, learning and visible progress. AI is unbundling that bundle.
  • Leaders can’t fix the global labor market, but they can redesign the first three years of a role so the learning survives when the routine work moves.

What’s happening with AI and entry-level jobs

On October 12 and 13, coverage of the IMF–World Bank annual meetings in Bangkok focused on a shared warning about young workers. Fortune reported on October 13 that Georgieva described AI’s effect on the job market as a “slow-moving tsunami” and said, “The people to worry about first and foremost are young people that are coming into the labor market.” Her reasoning was structural: routine, entry-level jobs have traditionally been the first step toward advancement.

Georgieva also pushed back on the simplest version of the story. According to Fortune, she said AI is not currently shrinking demand for people. “What it is doing is shifting demand for people now,” she said, adding, “That may not be the case in the future.” She cited the IMF estimate that around 40% of jobs worldwide will be augmented, downgraded or eliminated as AI advances. CNBC’s report from Bangkok added her figure that exposure is about 60% in advanced economies and 23% in low-income countries.

Singapore President Tharman Shanmugaratnam, who co-chairs the World Bank Jobs Council, made the point even more directly. Reuters, via The Star, quoted him saying “the first rung in employment, your first job upon graduation, is now seeing less demand,” and that “the evidence is already very clear, it’s clearest in the most AI-exposed sectors.” CNBC reported that he said that in the U.S., “for the first time in a century, demand for graduates has gone down,” and that he called for incentives for firms to hire fresh graduates.

Two details from Tharman stood out to me. First, CNBC reported that he described AI-driven displacement as happening “task by task,” which he said “gives us time” if workers can learn on the job. Second, Fortune quoted him on what is lost when a cohort can’t get started: “You lose a whole set of intangible attributes, and you lose trust in the future.”

Those are policy leaders speaking to governments. But both of those details land squarely on the desk of anyone who hires, trains or manages early-career people.

What this reveals: the first rung was always a bundle

In Chapter 10 of The Next Turn, “Fractional Work and the Unbundling of Jobs,” I argue that the full-time, fixed job is a construct. It bundled many different kinds of tasks together, partly because coordination used to be slow. AI and new ways of working make it possible to pull those tasks apart.

The entry-level job may be the clearest example of a bundle we never examined.

A first job carried routine production work: the summaries, the data cleanup, the first drafts, the reconciliations, the scheduling. It also carried something we rarely named. That routine work was how people learned the standards of the place. It was where they saw how decisions got made. It was where a manager could watch someone grow and decide they were ready for more.

When Tharman says displacement is happening “task by task,” that is unbundling. The routine tasks move first. The problem is that the learning was attached to those tasks. Take the tasks out without redesigning the role, and the learning falls out with them.

This is the second turn in the book, the structure of work. By that I mean how work actually flows: who or what does each task, in what order, and with what checks. The structure is changing faster than most organizations are redesigning the roles built on top of it.

Because the more work becomes unbundled, the more leadership shifts from managing roles to designing systems.

The Next Turn

Why it matters for leaders: the value exchange starts at the first rung

The first turn, the definition of work, shows up here too. By the definition of work I mean what people believe work is for, what it should provide and what it is worth.

In Chapter 5, “The Value Exchange (The 3-Year Problem),” I describe how that exchange has reordered. In an older system, people gave loyalty first and the organization tested it later. Now people assess value first and build loyalty only if the exchange proves itself. For an early-career employee, the most visible part of that exchange is growth. What will I learn here? What will I be able to do in three years that I can’t do today?

If the routine work that used to build that growth now goes to AI, and nothing replaces it, the exchange gets weaker exactly where it was already fragile. People can see that. Tharman’s phrase, “trust in the future,” is a macro version of something leaders already feel at the team level: people stop investing in a path they can’t see.

This is not about any one generation. Plenty of mid-career people are being asked to start over in new roles too. But young people entering the workforce feel the missing rung first, because they have no prior experience to stand on.

And here is the leadership trap. When the first rung disappears, it is tempting to raise the bar: hire only people who already have experience, and let someone else train them. That solves a staffing problem this quarter. It creates a talent pipeline problem in five years. If everyone waits for experience to arrive pre-built, no one is building it.

Because the real response to the three-year problem is not expecting more loyalty. It is building work that is easier to believe in.

The Next Turn

The leaders who handle this well will treat the first rung as something they design, not something the market hands them.

Your next turn

Pick one entry-level or early-career role on your team and try these this week:

  • Unbundle the role on paper. List every task the role did three years ago. Mark which ones AI now does or could do. Then ask: what was the person learning from each of those tasks?
  • Rebuild the learning on purpose. For every learning outcome that used to come from routine work, name a new way to get it: reviewing and correcting AI output, shadowing a decision, owning a small piece of a real outcome.
  • Make the path visible. Write down what someone in this role should be able to do at six months, one year and three years. If you can’t write it, they can’t see it either.
  • Ask where the saved time goes. If AI saves your newer people hours each week, decide whether that time goes to more output or to more learning. If no one decides, it defaults to output.
  • Check your hiring bar. Have you quietly raised experience requirements for entry-level roles? If so, who in your organization is now responsible for creating that experience?

Frequently asked questions

Is AI eliminating entry-level jobs?

Not in a simple way, according to the IMF. Georgieva said AI is currently shifting demand for people rather than shrinking it, while warning that this may not hold in the future. What leaders are seeing more often is that the routine tasks inside entry-level roles are changing first.

How should managers develop early-career employees when AI does the routine work?

Start by naming what the routine work used to teach: standards, context, judgment and how decisions get made. Then design new ways to build those skills directly, such as reviewing and correcting AI output, explaining choices to a manager, and owning small outcomes. Learning should be part of the role design, not a side effect of busywork.

Should companies just hire more experienced people instead?

That can solve a short-term need, but it shifts the cost of development to someone else and thins your own pipeline. If every employer waits for experience to arrive pre-built, no one builds it. A deliberate first rung is an investment in the people who will lead the work later.

The first rung is a leadership decision

Global institutions can debate policy. Inside your organization, the first rung is still yours to design. The routine work may move. The need to learn the work does not.

If someone joined your team this month at the very start of their career, what exactly would they learn in their first year, and who decided that?

You can find more on leading through both turns on the Next Turn blog.

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