Dr. Gleb Tsipursky – The Office Whisperer
Nirit Cohen – WorkFutures
Angela Howard – Culture Expert
Drew Jones – Design & Innovation
Jonathan Price – CRE & Flex Expert
What if entry-level jobs haven’t vanished?
What if we’re just not equipping young people with the skills those roles now call for?
For years, we told a generation that their future would be secured if they just mastered coding.
We restructured high schools around tech labs. Diminished humanities departments. Smirked at philosophy degrees. We insisted that fluency in logic, math, and engineering would lead to stable, well-compensated careers.
But now, artificial intelligence is doing the coding. And the jobs we built our education systems around? They’re the first being automated away.
The tough truth: we spent years preparing students to behave like machines, just as machines learned to do their jobs.
The issue isn’t that the first step on the career ladder is gone. It’s that it shifted, and we’re still looking for it in the old place.
A Change We Didn’t Anticipate
The early-career jobs that once served as stepping stones into roles like analyst, marketer, developer, or support staff are no longer the go-to entry. Employers are now leaning on AI to complete those tasks more efficiently and at lower cost.
The people still succeeding? They aren’t necessarily those with the newest diplomas or technical badges. They’re the ones with insight. Judgment. Human nuance.
According to the latest JOLTS numbers, U.S. hiring has dropped to a level not seen in over seven years. And the hit to early-career roles is even steeper — Revelio Labs found that white-collar entry-level postings dropped 12.7% in the past year. Jobs like software development and business analysis saw declines near 25%.
And this downturn is gaining speed. Anthropic CEO Dario Amodei recently cautioned that we’re “sleepwalking into mass unemployment,” warning that half of today’s entry-level knowledge jobs could be gone in five years. These aren’t manufacturing roles. They’re junior-level positions in finance, media, tech, and law — the exact tracks young professionals were steered toward.
This doesn’t signal the collapse of opportunity; it marks a necessary correction. One that exposes what we’ve been missing.
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We Focused on the Wrong Edge
AI can’t replicate lived experience. It doesn’t read social signals in a client pitch, weigh complex trade-offs, or assess team dynamics mid-crisis. It doesn’t know when to push, when to pause, or how to build trust across functions.
Those capabilities used to be built gradually — on the job, through exposure, mentorship, and real-world trial and error. But if AI is stepping into roles that once served as that training ground, we now face a new challenge: how to teach the human elements earlier.
While tech skills are being automated at lightning speed, AI still lacks imagination, empathy, moral reasoning, and contextual awareness. In a world powered by machines, it’s no longer about having the right answer. It’s about knowing the right questions, reading the full picture, and leading people through uncertainty.
We haven’t been preparing students for that. In the U.S., the percentage of degrees in the humanities has dropped from over 17% in the late 1960s to under 9% in 2022. Since the early 2000s, degrees in fields like English, history, and languages have nearly halved. Philosophy majors are now just 0.4% of all college graduates.
We treated this as evolution. As practicality.
Now we’re realizing it was a mistake.
Human Skills Are the Real Competitive Edge
The most crucial skills in this AI era aren’t “soft” — they’re essential.
Empathy. Persuasion. Ethical reasoning. Cultural literacy. Systems thinking. Creativity in uncertain terrain.
These skills are honed through literature, political science, anthropology, ethics, philosophy, which are disciplines we’ve steadily pushed to the margins. Not because of nostalgia, but because they’re strategic assets.
Because when AI can produce answers instantly, the advantage goes to those who know what matters, how to frame problems, and how to communicate meaning.
If we want to prepare future workers for a world where machines handle the tasks, we must reinvest in what makes us human. That means restoring the humanities — not as electives, but as core professional competencies.
It means broadening how we evaluate talent to include clarity, curiosity, and adaptability, not just credentials. And it means recalibrating STEM education to include ethics, systems awareness, and human-centered thinking.
This isn’t about going back in time. It’s about catching up with the world we’ve already stepped into.
We trained a generation for technical precision, just as that became commoditized by machines.
Now it’s time to invest in something AI can’t do: being deeply, powerfully human.
Because when the bots deliver the output, the real value lies with the person who sees the bigger story, and knows why it matters.
