Generative AI tools such as ChatGPT can fundamentally change the way investors process information. We probe the economic usefulness of these tools in summarizing complex cor-porate disclosures using the stock market as a laboratory. The unconstrained summaries are remarkably shorter compared to the originals, whereas their information content is amplified. When a document has a positive (negative) sentiment, its summary becomes more positive (negative). Importantly, the summaries are more effective at explaining stock market reac-tions to the disclosed information. Motivated by these findings, we propose a measure of information “bloat.” We show that bloated disclosure is associated with adverse capital mar-ket consequences, such as lower price efficiency and higher information asymmetry. Finally, we show that the model is effective at constructing targeted summaries that identify firms’ (non-)financial performance. Collectively, our results indicate that generative AI adds consid-erable value for investors with information processing constraints.

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