New York: young graduates now face higher unemployment than those who didn't go to college, and AI is the suspect

By New York Post · October 12, 2026.

Young New Yorkers with a college degree now have higher unemployment than those without one. According to US Bureau of Labor Statistics (BLS) data released by city Comptroller Mark Levine, New Yorkers aged 22 to 27 with a degree reached 7.3% unemployment in March 2026. Those of the same age without higher education stood at 7.1%.

It is the first time this has happened since January 2011, according to Levine's chart. Back then the gap was huge and ran the other way: 13.6% unemployment for those without a degree, versus 7.3% for those with one. According to the data, unemployment among graduates has been rising steadily since spring 2024. Among non-graduates, it has been falling since the fall of that same year.

Levine cautiously attributes the shift to AI. On X he called it “one more sign that AI is already affecting employment in New York” and asked how long we have to wait before treating it as something real. His office relies on a May report warning that the city is “sleepwalking into the AI era.” According to that report, AI could cost around 300,000 jobs and $14 billion in tax revenue. To reach that conclusion, it cites Anthropic data on the high concentration of AI use in computer and mathematical occupations. The office also estimates that AI could create some 52,000 new jobs through 2030 if the right measures are taken.

The national data point the same way. According to the BLS, in June the unemployment rate for young US graduates was 5.7%, versus 4.1% for all workers. According to the New York Fed, in 2010 recent graduates had 5.9% unemployment and all workers 9.3%. Today the situation has reversed.

**Our take.** The thesis we hold is this: a college degree no longer protects at the entry level, and AI is a plausible explanation, but not the only proven one. A gap of two-tenths of a point (7.3% versus 7.1%) in a sample from a single city and a single month is very small. It falls within normal statistical noise and does not by itself prove a cause. Moreover, the article offers no analysis separating the effect of AI from that of other factors. In general, interest rates, cooling hiring in finance and tech, and an oversupply of graduates also weigh on youth employment. What does carry weight is the trend: two years of divergence between the two groups and a similar pattern across the country.

What fits with what we have been seeing is the mechanism. AI first devours entry-level office tasks: drafting, summarizing, simple coding, preparing reports. These are precisely the jobs that allowed a recent graduate to learn the trade. New York, with its weight in finance, law, media and professional services, is the clearest example of that exposure. That is why Levine calls it a “canary in the coal mine.” In-person and manual sectors, which AI touches less, are better at absorbing those without degrees.

The short-term risk is real and should be stated plainly. A generation with student debt and a narrowing first rung on the career ladder could be scarred for years. Levine's proposed response, setting aside 16% of annual tax revenue in the city's reserve fund, is prudent, but it only cushions the blow. What is missing is reform of training: less reliance on degrees as a filter and more supervised practice, with AI as a tool young people are trained on rather than a substitute for their first job.

In the long term, our bet remains optimistic. If AI truly makes the production of goods and services cheaper, the resulting abundance will allow work to stop being an entry-level obligation and become a choice. But that transition is neither automatic nor painless. The New York data do not yet prove that AI is the cause, but they do tell us it is time to measure it seriously, before the gap becomes a structural problem.