Economists split on whether AI or remote work drives recent graduate unemployment rise

Recent graduates are experiencing higher unemployment rates than the general workforce, with 5.7% unemployment for 22-to-27-year-olds holding new degrees compared to 4.1% overall. The debate centers on whether AI or broader economic factors like remote work are the primary drivers. Economists like Erik Brynjolfsson argue AI is a contributing factor, pointing to a 16% relative employment decline for early-career workers in AI-exposed roles since late 2022. However, this decline is not uniform across all demographics, as older workers in similar fields have seen stable or growing employment.

The timing of the hiring slowdown complicates the narrative. David Deming notes that junior hiring declines began before the widespread adoption of tools like ChatGPT, suggesting other factors are at play. Remote work emerges as a key alternative explanation, with data from the New York Fed showing companies are less likely to hire recent graduates for remote roles. Training and supervision challenges in remote settings may disadvantage entry-level candidates, while senior candidates with established experience become more competitive for these positions.

AI’s role in hiring trends remains contested. Anders Humlum’s research found that companies investing heavily in AI actually increased entry-level headcount by 12% post-adoption, contradicting the idea that AI displaces junior roles. This suggests that AI’s impact on employment may be more nuanced, potentially augmenting rather than replacing certain jobs. The lack of consensus among economists reflects the difficulty in isolating AI’s effects from other variables like remote work, economic cycles, or industry-specific shifts.

For engineers, the implications are twofold. First, entry-level roles in AI-exposed fields may require additional adaptability, such as upskilling in AI tools or emphasizing in-person collaboration where possible. Second, the remote work trend may necessitate strategies to stand out in a crowded senior-dominated candidate pool, such as building portfolios or seeking hybrid roles. The debate underscores the need for granular data to clarify how automation and work policies interact to shape job markets.