We investigate the potential implications of Generative Pre-trained Transformer (GPT) models and
related technologies on the U.S. labor market. Using a new rubric, we assess occupations based on their
correspondence with GPT capabilities, incorporating both human expertise and classifications from GPT-4.
Our findings indicate that approximately 80% of the U.S. workforce could have at least 10% of their work
tasks affected by the introduction of GPTs, while around 19% of workers may see at least 50% of their
tasks impacted. The influence spans all wage levels, with higher-income jobs potentially facing greater
exposure. Notably, the impact is not limited to industries with higher recent productivity growth. We
conclude that Generative Pre-trained Transformers exhibit characteristics of general-purpose technologies
(GPTs), suggesting that as these models could have notable economic, social, and policy implications.