A Resume.org survey of close to 1,000 US business leaders, conducted earlier this year, found that 21% of companies say they have already frozen entry-level hiring specifically because of AI. The figure adds a concrete data point to a conversation that's often stayed at the level of anecdote, and the trajectory the survey describes is worth paying attention to even for job seekers outside the US.

The numbers get worse before they get better

The survey didn't stop at current behavior — it asked about intent. 36% of respondents said they expect to have stopped hiring entry-level workers by the end of this year, and nearly half, 47%, expect entry-level hiring to be eliminated at their company entirely by 2027. More than half of leaders surveyed, 51%, said their company will lay off workers in 2026 specifically because AI is consolidating or eliminating roles.

It's not always "AI did it alone"

One useful nuance in the data: among companies citing AI as a factor in cutting roles, only 21% call it the sole reason. 19% call it the primary driver, and 26% say it's one of several contributing factors alongside cost pressure, restructuring, or slower growth. That matters for how job seekers should interpret any individual hiring freeze or layoff announcement — AI is frequently the headline explanation, but it's rarely acting in isolation from ordinary business cycles.

Why entry-level roles specifically

Entry-level jobs have historically been where companies park repetitive, well-defined tasks — exactly the kind of work current AI tools handle reasonably well. Code review of simple bugs, first-draft documentation, basic data entry and cleanup, and first-pass customer support responses are all tasks that used to justify a junior headcount line and increasingly don't. The risk this creates is structural: if the traditional entry point into a profession narrows, the usual path from junior to senior gets harder to walk, not just for the people affected today but for the pipeline of experienced hires companies will want in five years.

What this means if you're early in your career

• Target roles where judgment, not task execution, is the job. Positions built around client relationships, ambiguous problem-solving, or decisions with real consequences are harder to automate than ones built around repeatable tasks.
• Make your AI fluency visible. Candidates who can demonstrate they already use AI tools to work faster and better are positioning themselves as a complement to automation rather than a competitor to it.
• Don't assume the pattern is uniform. Sectors and functions vary widely — some entry-level pipelines are shrinking fast, others are holding steady or even growing where human judgment and relationship-building remain central to the role.

The survey is US-focused, so the exact percentages won't map directly onto the Indian market, where entry-level hiring volumes and AI adoption curves differ. But the underlying shift — AI absorbing the easiest entry-level tasks first — is a global dynamic, and it's one worth factoring into how you think about your first few years in any field.

Read more on the survey findings.