Entry-Level Jobs Down 73%? How to Read the Data — and Build Experience Before Your First Job


"AI is killing entry-level jobs" has become a familiar headline. But what does the data actually show — and if you're early in your career, what should you do about it? In August 2026, Forbes reported on a study from hiring platform Cadient with a striking number: job openings that require no experience have fallen 73% in four years. Here's what's behind that figure, where its limits are, and how to build provable experience when nobody wants to give you your first chance.

The numbers: entry-level openings down 73%

Cadient, an AI-powered hiring platform, tracked 7,984 salaried job openings across a stable panel of employers from 2022 to 2026. As reported by Forbes (August 2, 2026), the key findings were:

  • Openings requiring no experience dropped 73% over four years
  • Inexperienced candidates are now viable for roughly 1 in 50 openings, down from 1 in 15 in 2022
  • Overall salaried openings fell 27%
  • Applications per position roughly tripled
  • Roles requiring senior-level experience doubled

Separately, New York Fed data shows unemployment for recent college graduates (ages 22–27) at 5.6%, above the 4.2% overall rate — an unusual inversion where the youngest, most educated workers face the tougher market.

Before you panic: what this data can and can't tell you

Three caveats matter. First, this is one platform's panel of employers — useful as a signal, but not a census of the whole labor market. Second, the decline can't be attributed to AI alone: interest rates, cautious hiring, and economic cycles all play a role, and correlation is not causation. Third, "entry-level openings fell" is not the same as "no one inexperienced gets hired" — it means the odds shifted, sharply.

Still, Cadient CEO Bill Mastin's framing is worth taking seriously: the real issue isn't that entry-level jobs are disappearing, but that employers increasingly expect candidates to arrive with experience before they're given the opportunity to gain it. Applicant tracking systems filter résumés before a human ever reads them, and candidates with nothing verifiable on paper get screened out first.

The new bottleneck: your first provable experience

If the entry ramp is narrowing, the question changes from "will there be jobs?" to "where do I get my first evidence of competence?" The tasks juniors traditionally learned on — first drafts, research summaries, basic analysis — are exactly what AI tools now do quickly. That doesn't make junior people useless; it means the market increasingly pays for what you can demonstrate, not what you might learn on the job.

Four ways to build evidence without a job title

  • Ship things publicly. A portfolio site, a data analysis write-up, a small tool or automation — artifacts someone can inspect beat adjectives on a résumé. If you built it with AI assistance, be ready to explain your process; that's a skill in itself.
  • Collect short stints of real work. Internships, freelance gigs, contract projects, volunteer work for a nonprofit — the employment format matters less than being able to say "I did this for a real organization."
  • Turn learning into verifiable credentials. Certificates, micro-credentials, and open badges give screening systems something concrete to match. Employer education benefits can cover much of the cost.
  • Position yourself as the person who uses AI well. In interviews, a specific story — "here's a workflow I automated, here's what I checked by hand" — partially substitutes for years of experience.

What not to do

You'll find advice about gaming résumé screeners — hidden keywords in white text, exaggerated titles. Skip it. Discovery means instant rejection, and the tactics don't survive a first-round conversation. The honest version works better: mirror the actual language of the job posting where it truthfully describes your experience, and put your evidence up front.

Frequently asked questions

Will entry-level hiring recover?

Unclear. Some economists see a temporary adjustment as companies figure out AI; others see a structural reset. Either way, candidates with verifiable output are better positioned in both scenarios.

Does this affect all fields equally?

No. The squeeze is most visible in white-collar work where AI handles routine tasks — admin, basic analysis, junior writing and coding. Roles requiring physical presence, licensure, or high-touch human interaction have been less affected so far.

Is a degree still worth it?

A degree alone opens fewer doors than it used to, but it still matters for many employers and fields. The bigger shift is that a degree now needs company: projects, credentials, and work samples that prove you can already do something.

Related on AI Learning Lab: The 56% AI Salary Premium: What PwC's Numbers Really Mean for Your Career · How to Get AI Training Paid For: The $5,250 Employer Education Benefit Explained · Freelancers Who Use AI Earn 34% More

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