They pick the "safe" degree. Not because they want to. Because they're scared.
I've been guiding sixth-formers through university applications long enough to see the pattern. A student comes in genuinely excited about history, or literature, or sociology. Then they spend a week doom-scrolling headlines about graduate unemployment and emerge convinced they should study something with "management" in the title.
I understand the fear. The debt is real. The pressure from parents is real. And the "lost generation" coverage lands hard when you're 17 and trying to map out the next 40 years of your life.
But here's what the data actually shows — and I wish more people talked about this:
Around 88–89% of graduates are in work or further study within 15 months of finishing their degree. Not eventually. Within 15 months. The image of arts graduates stacking shelves in perpetuity simply isn't what the numbers reflect.
Yes, there's a gap. Science graduates enter high-skilled employment at roughly 82%; non-science graduates at around 72%. That's worth knowing. Early-career salaries follow a similar slope, with medicine, engineering, and economics at the top. But a gap is not a cliff edge. Most humanities graduates find meaningful work. The difference tends to show up in starting salary and career trajectory — not in some binary of "employable" versus "unemployable."
What the headlines never tell you is this: the students who tend to do best — financially and otherwise — are the ones who chose something they could actually sustain. Passion isn't soft advice. It's strategic. A degree you hate studying translates, fairly predictably, into a career you'll want to leave.
So when a student sits across from me, terrified of making the wrong choice, I tell them the same thing every time: pick the subject you can still stand thinking about on a Monday morning. That enthusiasm compounds. It shows in interviews, in postgraduate choices, in the lateral moves that build unusual careers.
University isn't only a labour market transaction. Three years of deep, focused thinking on something that matters to you shapes how you reason, what you notice, and who you become. Those things have market value too — even if no salary table captures them cleanly.
The jobs apocalypse makes for a great headline. It just doesn't make for good advice.
Apollo Economist Sees 'Zero Evidence' of AI-Driven Job Losses Amid Corporate Layoff Claims
Concerns that artificial intelligence will displace workers may be overstated—at least according to Torsten Sløk, chief economist at Apollo Global Management.
In a recent blog post, Sløk asserted there is "zero evidence of job losses because of AI," pointing to data from the ADP National Employment Report. Rather than eliminating roles, he argues, companies are actively seeking talent with AI expertise.
"Many firms are hiring AI implementation experts, and the data center buildout is putting upward pressure on salaries for AI specialists—and on prices for semiconductors, equipment, and energy," Sløk noted. "The bottom line is that the AI spending boom is stoking both employment and inflation."
This perspective aligns with his April analysis, in which he wrote: "Cheaper inputs don't shrink industries. Instead, AI is going to increase both productivity and employment."
Recent labor data appears to support this outlook: the latest ADP report showed private-sector employers added nearly 110,000 jobs in April alone.
A Divide Between Optimism and Reality
Despite Sløk's confidence, anxiety about AI's impact on employment remains widespread—fueled in part by leaders within the AI industry itself. While Anthropic CEO Dario Amodei and OpenAI CEO Sam Altman have recently moderated their public messaging ahead of anticipated IPOs, both have previously warned that AI could disrupt entire categories of work. Amodei notably suggested last year that AI might eliminate half of all entry-level white-collar positions.
Sløk's analysis has found resonance among prominent voices. Box CEO Aaron Levie, Dell CEO Michael Dell, and White House AI and Crypto Czar David Sacks all expressed agreement with his assessment in social media posts over the weekend. Goldman Sachs CEO David Solomon advanced a similar argument in a recent *New York Times* op-ed.
Further bolstering the optimistic view, an EY survey of 240 financial services CEOs found that roughly 60% believe AI investments will maintain or expand their workforce headcount in 2026.
The Layoff Counter-Narrative
These projections, however, appear at odds with recent corporate actions. At least a dozen major companies have explicitly cited AI as a factor in workforce reductions this year.
In February, Block CEO Jack Dorsey announced a significant downsizing—from over 10,000 employees to under 6,000—attributing the move partly to AI-driven efficiencies.
> "We're already seeing that the intelligence tools we're creating and using, paired with smaller and flatter teams, are enabling a new way of working which fundamentally changes what it means to build and run a company," Dorsey wrote in a memo shared on X. "I had two options: cut gradually over months or years as this shift plays out, or be honest about where we are and act on it now."
Other companies—including Cisco, Atlassian, Cloudflare, Coinbase, IBM, and Snap—have similarly referenced AI integration as a rationale for recent layoffs.
Industry Leaders Push Back on "AI Washing"
Not all tech executives accept this narrative. NVIDIA CEO Jensen Huang, a central figure in the AI infrastructure boom, has criticized leaders who attribute layoffs to AI adoption.
"I think the narrative that connects AI to job loss for many of the CEOs that are doing it is just too lazy," Huang told reporters in Singapore last week.
Sam Altman has gone further, labeling the practice of citing AI to justify staff reductions as "AI washing"—a term suggesting companies use the technology as a convenient scapegoat for broader restructuring decisions.
The Jevons Paradox at Work
In his latest analysis, Sløk frames the current employment landscape through the lens of the *Jevons paradox*—an economic principle stating that as technology improves the efficiency of resource use, overall consumption of that resource tends to rise, not fall.
Applied to labor, Sløk argues, AI makes human workers more productive, thereby increasing demand for their skills.
"It is Jevons paradox playing out in real time: cheaper technology is creating more demand and more jobs," he concluded.
As the debate intensifies, one thing remains clear: while AI reshapes how work gets done, its ultimate impact on employment will depend less on the technology itself—and more on how organizations choose to deploy it.