According to Business Insider, a new analysis from Dario Perkins of TS Lombard shows unemployment among new US labor force entrants has jumped over 2.5 percentage points since 2023. This starkly contrasts with older workers, whose jobless rates have stayed flat. Perkins directly counters the narrative that AI deployment is causing this, stating sectors with high AI exposure aren’t seeing bigger unemployment spikes. He identifies three old-school reasons: post-pandemic workforce normalization, policy uncertainty, and Trump-era tariffs squeezing profits. Meanwhile, a separate Goldman Sachs report from August notes the unemployment rate for 20- to 30-year-olds in tech has risen nearly 3 percentage points since early 2024.
The Real Culprits Are Boring
Here’s the thing: the AI story is sexy. It’s a dramatic, futuristic explanation for economic pain. But Perkins’ argument is way more mundane, and honestly, more convincing. Companies went on a hiring binge after the pandemic, and now they’re hitting pause. Add in the anxiety of an election year and tariffs that eat into margins, and you have a perfect recipe for a hiring freeze. It’s not that robots are taking the entry-level jobs; it’s that the jobs just… aren’t being posted. This is basic business cycle stuff, dressed up in a scary new tech costume.
Why The AI Narrative Sticks
So why is everyone so quick to blame AI? Perkins nails it: “AI” has become a synonym for “cost cutting” in boardrooms. When a CEO says they’re leveraging AI for efficiency, Wall Street cheers. It sounds proactive and innovative. But often, that “efficiency” just means a hiring slowdown or pushing current staff to do more. The Goldman Sachs warning about “jobless growth” feeds right into this fear. It creates a powerful, simple story. But correlation isn’t causation. The economy might be strong overall, but that strength isn’t translating into new job creation right now, especially for newcomers.
young”>A Tough Break For The Young
This situation absolutely squeezes young people the most. They’re the new entrants. When hiring freezes happen, they’re the first to feel it because they’re not in the system yet. Older workers are already embedded. But there’s a sliver of good news in this analysis. If the problem is cyclical weak hiring and not structural AI replacement, then the fix is clearer. When the economy eventually reaccelerates and companies get confident again, the spigot should turn back on. The skills they’ve learned won’t be obsolete. They’re just stuck in a brutal waiting game. The question is, how long will that wait be?
