The Entry-Level Crisis: How to Lead Through AI Disruption

Anthropic CEO Dario Amodei caused commotion, at least in my corner of the internet, when he ​told​ Axios that “AI may wipe out 50 percent of entry-level white-collar roles within five years.”

Fresh data suggests he might be right:

• Big Tech graduate hiring is down by 50% since 2019 (​SignalFire​).
• Meta’s Mark Zuckerberg ​said​ AI will soon handle “mid-level engineer” work.
• ServiceNow agents already ​resolve​ 80% of support tickets unaided.
• An EY ​survey​ reveals that 48% of tech executives are deploying agent-based AI.
• Salesforce is ​redeploying​ 500 service reps into “data-plus-AI roles.”

Together, the signals point to a “broken bottom rung on the career ladder,” as LinkedIn’s Chief Economic Opportunity Officer, Aneesh Raman, ​wrote​ in The New York Times:

“In tech, advanced coding tools are creeping into the tasks of writing simple code and debugging — the ways junior developers gain experience. In law firms, junior paralegals and first-year associates who once cut their teeth on document review are handing weeks of work over to A.I. tools to complete in a matter of hours. And across retailers, A.I. chatbots and automated customer service tools are taking on duties once assigned to young associates.” – Aneesh Raman, Chief Economic Opportunity Officer, LinkedIn

So what does the entry-level job of the future look like, and how do we (workers and companies) get there?

Let’s dive in.

The New Entry-Level Job

I liked ​Josh Bersin​’s ​counter​ to Amodei’s prediction that entry-level jobs are about learning and building a pipeline, not just cheap labor. And that cutting them creates long-term skill gaps.

This is something LinkedIn’s Aneesh Raman also highlighted: getting started later means less money and more inequality.

I’m also puzzled by what entry-level jobs are, anyway. Any first job that people (eventually) take is entry-level. How can they go away?

But yes, if we interpret those as the kind of roles Raman describes, I do think Amodei’s “50%” is directionally right. Jobs where you’re just copy-pasting, summarizing, or creating first drafts will become obsolete with AI.

However, in its place will be ‘first roles’ as ‘AI leaders' that young candidates are ideally suited for.

They enter the workforce as AI natives, and in fact, can teach today's leaders a lesson or two (reverse mentoring).

This is a place where graduates can actually have a significant advantage: Sam Altman recently remarked that younger AI users often tap it as ​a new kind of operating system​, rather than a Google replacement.

These are the kind of people that employers are hungry for, as evidenced by Zapier CEO Wade Foster, who stated that 100% of new hires must be fluent in AI.

Because, as I recently stressed in my articles ​Prompt Engineering Isn’t Dead​ and ​You’re Only Using 10% of ChatGPT​, AI still needs direction.

Today’s models are incredibly powerful. I’ve been working more with o3, and it amazes me what a reasoning model + tools can do. But no matter how impressive, they still need direction.

“The machine can do anything, now what do you want them to do?”

Tapping AI as a team member and prompting them well is key, alongside proficiency in tool fluency, to start or continue any career.

Even Amodei ​told​ Anderson Cooper so: the best hedge to future disruptions is simply “learn AI.”

That message is loudest for fresh graduates who now know what employers value:

1. Baseline expectation: Do you know how to prompt, set up a simple assistant, and leverage different models? (See ​my new ChatGPT course​ if you need help.)
2. Become a SuperWorker: Use ​my GED-RT framework​ (General, Error-friendly, Digital, Recurring, Toil) to identify tasks that AI (beyond ChatGPT) can handle today.
3. Show real projects: custom GPTs, automations, and prompt libraries: proof you can tailor these models for real productivity and impact. (the stuff we do in the ​Lead with AI executive bootcamp​.)

Do so, and graduates may even agree with PwC, which ​said​ they’re “lucky to be starting their careers as AI accelerates.”

Companies

But this discussion isn’t just about what people can do. It’s also a call to action for companies to get serious about AI at all levels:

• Name the risk in entry-level roles. As OpenAI writes in its playbook ​Identifying & Scaling AI Use Cases​, jobs vanish only for people who never use AI.
• Recruit new team members who are AI-fluent, or at least (like I do), hire for the willingness, mindset, and attitude to work with AI.
• Encourage reverse mentoring. ​Sophie Wade​ said ​in an interview​ that “Many leaders are missing out on the contributions of their youngest employees who have a feeling for the power of technology that we just can’t have.” Tap into that.
• Upskill throughout. As OpenAI suggests, teach at least the six AI primitives (content, research, code, data, ideation, and automation).
• Get everyone building. Run a GED-RT sweep team-by-team to find low-joy, high-repeat tasks, and find quick wins just as Moderna went from ​750 to 3,000 GPTs​ and J&J ​pruned 900 experiments​ down to the 15% that drove 80% of value.

SHRM Foundation Chair and Future of Work expert ​Edie Goldberg​ underscored the imperative for companies to rethink entry-level positions in exclusive commentary for this newsletter:

“Entry-level jobs are changing, but we need to rethink how people learn the business and build functional expertise. Research shows that AI is especially helpful for lower-performing employees—often those who are just starting out—because it provides access to the knowledge that drives success. Entry-level roles aren’t disappearing, but they are evolving. We need to evolve our thinking with them.” – Edie Goldberg, the Immediate Past Chair of the SHRM Foundation Board of Directors

Don’t Get Left Behind

The bottom line is that AI will eventually disrupt all jobs, and therefore, AI mastery is critical for everyone, from recent graduates to seasoned executives.

Students and graduates should prepare themselves to be as attractive in the market as possible by studying up on AI.

Companies should ensure they’re ready to hire those who are most likely to drive AI adoption and culture.

So, pick one GED-RT task this week, replace it with a prompt-plus-tool workflow, and demo the result—then repeat. The ladder may be shorter, but it climbs faster if we rebuild it now.