Stanford’s Institute for Human-Centered AI’s 2026 AI Index says that employment for software developers ages 22-25 has fallen nearly 20% since 2024. The data comes from ADP payroll records covering millions of workers.
As AI tools take on more of the routine work, the job market for new graduates and Gen-Z professionals has tightened sharply. Workers aged 22-25 in AI-exposed occupations, including customer service and accounting, saw a 13% relative employment decline. However, workers aged 30 and over in the same occupations saw headcount grow.
Headlines about these numbers tend to frame the trend as a job market problem for young workers. The less visible and far more consequential problem is what happens inside the organizations cutting those roles into the future.
Entry-level jobs served as the apprenticeship layer, the place where future leaders built judgment through real stakes, and that’s the layer AI is now absorbing.
The Learning-By-Doing Gap
For many organizations, the classic path to leadership ran through the work itself.
The analyst buried in spreadsheets for two years learned to recognize a number that was off. The junior consultant who drafted 150 presentations before making partner learned what actually drives client decision-making, a lesson that only comes from real-world experience. This is judgment, and it only gets built through doing. The sales rep who knocked on doors learning how to deal with and overcome customer objections.
AI coding tools are easily taking on the boilerplate. AI is drafting the first version of the analysis. The tasks that used to fill a new hire’s first year are being automated faster than leadership pipelines are being redesigned.
The Invisible Cost Now Will Be a Tsunami Tomorrow
The manufacturing and construction industries offer a preview of what happens when apprenticeship pipelines thin too fast. Productivity held steady, even improved, in the short term. The gap showed up five years later, when mid-level roles requiring clear judgment were hard to fill and institutional knowledge had walked out the door.
IBM saw the leadership pipeline risk and proactively acted. IBM’s Chief Human Resources Officer Nickle LaMoreaux recently announced the company would triple its entry-level hiring in the United States, explicitly for “jobs we’re being told AI can do.” Her argument was that software tools can be learned in weeks, but the judgment to deploy them well takes years to build. “The companies three to five years from now that are going to be the most successful are those companies that doubled down on entry-level hiring in this environment,” LaMoreaux said.
IBM also redesigned what those roles look like. Since AI handles most routine coding tasks, junior developers now spend more time in customer-facing work and complex problem-solving, building judgment in situations where AI falls short.
What Leaders Can Do Now
- Map your judgment pipeline. Identify which entry-level roles have traditionally built the judgment your mid-level leaders rely on and assess whether AI is now absorbing that developmental layer.
- Restructure entry-level roles. Follow IBM’s approach and redesign junior positions toward customer interaction, AI oversight, and judgment-intensive work, preserving the development ladder even as AI absorbs routine tasks.
- Design hands-on experiences. If junior hiring is shrinking, identify the specific experiences those roles generated and create intentional development programs to replace them before a judgement gap shows up in your leadership bench.
AI is commoditizing the task layer of work. The judgment layer will become competitive differentiation. Said another way, knowledge is now a commodity. Judgment is becoming scarce.
This Week
In my book Experiential Intelligence, I describe the intelligence built from everything you’ve experienced as consisting of your mindsets, abilities, and know-how. Before your next workforce planning conversation, ask which decisions in your organization only get made well by someone who has been in the trenches. Then identify one role that’s traditionally developed that judgment and map whether their developmental path has been or is being absorbed by AI. If so, fill the gap with learning opportunities for others on your team to ensure you can backfill the decision-making needed for the future.
AI may be doing the data heavy work. The judgment that used to come from doing it is now the imperative to build and replace.
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