Reinforcing Learning? Student Responses to AI Labour Market Disruption

As large language models (LLMs) reshape the labour market, a less-explored but equally important area of concern is the educational sector: are prospective students adjusting their educational choices in response? If they are, these decisions will shape the future supply of skills in the workforce; if they are not, does this signal a possible lag in adjusting their expectations? Both cases could provide insights for policy intervention. We use the public release of ChatGPT in November 2022 as an exogenous shock. We construct an AI exposure index linking degree programmes to graduate occupations and combine it with UCAS application data covering 2019–2025. Using a Two-Way Fixed Effects (TWFE) framework, we estimate both baseline difference-in-differences and dynamic event study specifications and find that applications to more highly AI-exposed fields have increased relative to less exposed fields since 2022, with effects growing over time. We find no impact on whether students choose to attend university overall. These findings suggest that students may view AI exposure as an opportunity rather than a threat, though underlying pre-treatment demand trends in high-exposure fields such as computer science may also contribute to the observed pattern.