Generative AI, Managerial Expectations, and Economic Activity

Manish Jha, Jialin Qian, Michael Weber and Baozhong Yang

No 35949, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: Using generative AI, we extract managers’ economic expectations from over 120,000 corporate conference call transcripts. The resulting AI Economy Score predicts GDP growth, production, employment, and wages five or more quarters ahead, beyond survey forecasts and other existing measures. Industry- and firm-level scores capture sector- and firm-specific activity, and a composite of firm, industry, and macroeconomic expectations further improves forecasting power and horizon. Predictability concentrates among historically more accurate, less biased managers, consistent with an information rather than a noise channel. Managerial expectations thus offer incremental insights into economic activity, with implications for macro- and microeconomic decision-making.

JEL-codes: C81 D2 E2 E3 E44 (search for similar items in EconPapers)
Date: 2026-10
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Working Paper: Generative AI, Managerial Expectations, and Economic Activity (2025)
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