Market Mismatch Mitigated: According to Oxford Economics and Goldman Sachs, AI deployment coincided with severe labor shortages in exposed fields, meaning it is currently acting as a labor-augmenting tool rather than a mass displacer.

The current wave of layoffs in tech and other US sectors has been met with a uniform explanation from corporate boardrooms: artificial intelligence. Just recently, networking giant Cisco joined the trend, justifying its job cuts by a corporate pivot toward AI. However, a comprehensive study by researchers at the New York Fed paints a far more complicated picture, suggesting executives have simply found a highly convenient scapegoat.

Researchers scrutinized US job vacancies using an automation-vulnerability metric developed by economists at Anthropic, isolating roles heavily exposed to AI—such as programmers, customer service representatives, and data entry clerks. The goal was to determine if hiring patterns fundamentally shifted before and after the generative AI boom of late 2022.

When Did the Slowdown Start? The Post-ChatGPT Divergence Myth

The study’s baseline premise was straightforward: if AI was the true culprit behind the hiring freeze and layoffs, employment trends for high-exposure and low-exposure jobs should have tracked together until late 2022, only to aggressively diverge afterward. In reality, the findings revealed a completely different timeline.

The relative decline in job postings for AI-exposed positions began in early 2022—months before the public even knew what ChatGPT was. Furthermore, the gap in labor demand between high-exposure and low-exposure roles actually stabilized after 2023. “This trajectory is at odds with AI gradually displacing exposed occupations,” the researchers noted.

The Entry-Level Myth: Everyone Is in the Same Boat

One of the most persistent narratives over the past year is that corporations have stopped hiring entry-level workers because AI can handle basic tasks. The New York Fed checked the depth of job listings and discovered that the hiring slowdown was not concentrated in junior roles; senior-level postings in those same vulnerable sectors dropped at a nearly identical rate.

While unemployment among young workers and recent college graduates has ticked upward since 2022, researchers emphasize this is a symptom of a broader macroeconomic slowdown and rising interest rates, rather than an automated market closing its doors to the next generation.

The Outlook: High Churn, Not Mass Unemployment

A separate analysis by Oxford Economics supports the Fed’s findings. Chief US Economist Michael Pearce notes that while AI adoption has become mainstream, actual aggregate usage remains relatively low, explaining the muted impact on productivity and the overall labor market. In fact, the unemployment rate for AI-exposed occupations has actually ticked downward in recent months, moving in line with broader labor-market improvements.

The only corner of the market experiencing a localized earthquake is the information sector. There, both hiring and firing rates have surged simultaneously—a phenomenon known as high labor churn—while the net change in jobs remains virtually flat.

Goldman Sachs economists conclude that the first stage of AI deployment was fortuitously timed, coinciding with severe labor shortages in the most exposed fields, which ultimately prevented an employment crisis. However, the next stage of corporate deployment will likely require far more adaptation from the workforce, as employees must learn to pivot alongside the evolving technology.