Generative AI for Analysts

TL;DR

This paper examines how generative AI, exemplified by FactSet's 2023 platform launch, enhances financial report quality and breadth but also introduces increased forecast errors and cognitive challenges for analysts.

Contribution

It provides empirical evidence on the effects of generative AI in financial analysis, highlighting productivity gains and cognitive limitations.

Findings

Reports become 40% richer in information sources

Topical coverage increases by 34%

Forecast errors rise by 59% with AI adoption

Abstract

We study how generative artificial intelligence (AI) transforms the work of financial analysts. Using the 2023 launch of FactSet's AI platform as a natural experiment, we find that adoption produces markedly richer and more comprehensive reports -- featuring 40% more distinct information sources, 34% broader topical coverage, and 25% greater use of advanced analytical methods -- while also improving timeliness. However, forecast errors rise by 59% as AI-assisted reports convey a more balanced mix of positive and negative information that is harder to synthesize, particularly for analysts facing heavier cognitive demands. Placebo tests using other data vendors confirm that these effects are unique to FactSet's AI integration. Overall, our findings reveal both the productivity gains and cognitive limits of generative AI in financial information production.