Source: Bradshaw, Ma, Yost & Zou (2026) — “Generative AI Use by Capital Market Information Intermediaries: Evidence from Seeking Alpha”
At first this sounds like a technical finance question. Then you look closer and realise it is also a question about attention, incentives, and whether people are using information or just being impressed by it.
After ChatGPT launched in November 2022, the share of AI-generated articles on Seeking Alpha — a platform where individual analysts publish financial research on specific companies — rose sharply to 13.5% of all articles. Then Seeking Alpha banned AI use in late 2023, treating it as equivalent to plagiarism. The ban gave researchers a before-and-after structure to study what AI actually did to the production and quality of financial analysis. The headline results contain a tension that’s worth thinking about carefully. On productivity: authors who adopted AI became significantly more productive. They published more articles and covered more companies than non-adopters. AI made it cheaper and faster to produce financial commentary, and authors responded by producing more. On informativeness: AI-generated articles were less informative than human-written articles. When measured by market reactions — trading volume and abnormal returns around article publication — AI articles elicited smaller responses. The market apparently recognised that these articles contained less new information. So you have a technology that increases quantity while reducing quality per unit. The question is what the net effect is.
In plain English, that is why the result matters beyond the chart. It changes where people should look, what they should question, and which comfortable assumption probably needs to be retired.
So I would not read this as a neat technology story. It is a messy information story. The tools improve, but people still have to decide what deserves attention. Annoying, but true.