Winners and losers of generative AI: Early Evidence of Shifts in Freelancer Demand

This is the authors' abstract. We don't add key points for this paper.

We examine how ChatGPT has changed the demand for freelancers in jobs where generative AI tools can act as substitutes or complements to human labor. Using BERTopic we partition job postings from a leading online freelancing platform into 116 fine-grained skill clusters and with GPT-4o we classify them as substitutable, complementary or unaffected by LLMs. Our analysis reveals that labor demand increased after the launch of ChatGPT, but only in skill clusters that were complementary to or unaffected by the AI tool. In contrast, demand for substitutable skills, such as writing and translation, decreased by 20–50% relative to the counterfactual trend, with the sharpest decline observed for short-term (1-3 week) jobs. Within complementary skill clusters, the results are mixed: demand for machine learning programming grew by 24%, and demand for AI-powered chatbot development nearly tripled, while demand for novice workers declined in general. This result suggests a shift toward more specialized expertise for freelancers rather than uniform growth across all complementary areas. • LLM-based clustering shows ∼ 10% of job postings are substitutable by GenAI. • GenAI cut demand for substitutable skill clusters by up to 50% in short-term roles. • Demand for some complementary AI clusters like machine learning increased. • Demand for novice workers in complementary roles declined. • Aggregate freelance demand did not decrease after the ChatGPT launch.