The tasks AI handles best — routine research, first drafts, data cleanup, standard answers — are often the tasks that junior staff used to learn on. That makes entry-level roles the first place to look.
What is happening
- A Gartner survey of 110 HR leaders (4Q25) found 22% of CHROs report that at least one business leader in their organization has stopped hiring for entry-level roles because of AI automation. The same survey found 95% of organizations implemented AI in the past year, but only one in five realized significant or transformational value.
- Stanford researchers find employment of workers aged 22–25 in the most AI-exposed occupations about 19% below trend, concentrated where AI substitutes for tasks.
Why cutting the entry level is risky
Gartner warns that organizations that cut early-career pipelines altogether may later have to hire experienced talent externally at premium cost, instead of developing it. Today's juniors are tomorrow's managers and experts.
What to do instead
Gartner recommends three moves:
- Shift tasks: analyse how AI changes work and give early-career employees higher-value tasks earlier — including supervising AI outputs.
- Activate support structures: build adaptable skills, not only narrow technical ones.
- Build safety nets: tools, guidance and peer support so juniors can handle complex, ambiguous work without costly errors.
Redesign the first two years
- Rewrite entry-level job descriptions around judgment, customer contact and AI supervision.
- Pair juniors with experienced staff on real problems; use AI for practice and feedback.
- Track entry-level hiring, progression and retention as part of your AI dashboard.