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Generative AI for Analysts

Author

Listed:
  • Jian Xue
  • Qian Zhang
  • Wu Zhu

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.

Suggested Citation

  • Jian Xue & Qian Zhang & Wu Zhu, 2025. "Generative AI for Analysts," Papers 2512.19705, arXiv.org.
    • Handle: RePEc:arx:papers:2512.19705
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    References listed on IDEAS

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    1. Ping Wang & Tsz-Nga Wong, 2025. "Artificial Intelligence and Technological Unemployment," NBER Working Papers 33867, National Bureau of Economic Research, Inc.
    2. Li, Junjun & Wu, Tong & Hu, Boqiang & Pan, Dongliang & Zhou, Yaqiong, 2025. "Artificial intelligence and corporate ESG performance," International Review of Financial Analysis, Elsevier, vol. 102(C).
    3. Yan He & Takehiko R. Saito & Hiroyuki Ekawa & Ayumi Kasagi & Yiming Gao & Enqiang Liu & Kazuma Nakazawa & Christophe Rappold & Masato Taki & Yoshiki K. Tanaka & He Wang & Ayari Yanai & Junya Yoshida &, 2025. "Artificial intelligence pioneers the double-strangeness factory," Nature Communications, Nature, vol. 16(1), pages 1-9, December.
    4. Hirshleifer, David & Levi, Yaron & Lourie, Ben & Teoh, Siew Hong, 2019. "Decision fatigue and heuristic analyst forecasts," Journal of Financial Economics, Elsevier, vol. 133(1), pages 83-98.
    5. Shihao Gu & Bryan Kelly & Dacheng Xiu, 2020. "Empirical Asset Pricing via Machine Learning," Review of Finance, European Finance Association, vol. 33(5), pages 2223-2273.
    6. Athina Karvounaraki & Alexis Stevenson & Isabelle Labrosse & David Campbell & Henrik Karlstrøm & Eric Iversen & Lili Wang & Ad Notten, 2025. "The Use of Generative Artificial Intelligence in Research," EU research and innovation paper series KI-01-25-084-EN-N, Directorate General for Research and Innovation (DG RTD) of the European Commission.
    7. Jian Chen & Guohao Tang & Guofu Zhou & Wu Zhu, 2025. "ChatGPT and Deepseek: Can They Predict the Stock Market and Macroeconomy?," Papers 2502.10008, arXiv.org.
    8. Jules H van Binsbergen & Xiao Han & Alejandro Lopez-Lira, 2023. "Man versus Machine Learning: The Term Structure of Earnings Expectations and Conditional Biases," The Review of Financial Studies, Society for Financial Studies, vol. 36(6), pages 2361-2396.
    9. Hainmueller, Jens, 2012. "Entropy Balancing for Causal Effects: A Multivariate Reweighting Method to Produce Balanced Samples in Observational Studies," Political Analysis, Cambridge University Press, vol. 20(1), pages 25-46, January.
    10. Elizabeth Blankespoor & Ed deHaan & Christina Zhu, 2018. "Capital market effects of media synthesis and dissemination: evidence from robo-journalism," Review of Accounting Studies, Springer, vol. 23(1), pages 1-36, March.
    11. Anton Korinek, 2023. "Generative AI for Economic Research: Use Cases and Implications for Economists," Journal of Economic Literature, American Economic Association, vol. 61(4), pages 1281-1317, December.
    12. Musaib Ashraf, 2025. "Does automation improve financial reporting? Evidence from internal controls," Review of Accounting Studies, Springer, vol. 30(1), pages 436-479, March.
    13. Tao Tu & Mike Schaekermann & Anil Palepu & Khaled Saab & Jan Freyberg & Ryutaro Tanno & Amy Wang & Brenna Li & Mohamed Amin & Yong Cheng & Elahe Vedadi & Nenad Tomasev & Shekoofeh Azizi & Karan Singha, 2025. "Towards conversational diagnostic artificial intelligence," Nature, Nature, vol. 642(8067), pages 442-450, June.
    14. Lynn Wu & Bowen Lou & Lorin M. Hitt, 2025. "Innovation Strategy After IPO: How AI Analytics Spurs Innovation After IPO," Management Science, INFORMS, vol. 71(3), pages 2360-2389, March.
    15. Eleanor W. Dillon & Sonia Jaffe & Nicole Immorlica & Christopher T. Stanton, 2025. "Shifting Work Patterns with Generative AI," NBER Working Papers 33795, National Bureau of Economic Research, Inc.
    16. Jonathan Wang & Donald A. Redelmeier, 2025. "Forewarning Artificial Intelligence about Cognitive Biases," Medical Decision Making, , vol. 45(7), pages 913-916, October.
    17. Cong William Lin & Wu Zhu, 2025. "Divergent LLM Adoption and Heterogeneous Convergence Paths in Research Writing," Papers 2504.13629, arXiv.org.
    18. Lawrence D. Brown & Artur Hugon, 2009. "Team earnings forecasting," Review of Accounting Studies, Springer, vol. 14(4), pages 587-607, December.
    19. Erik Brynjolfsson & Danielle Li & Lindsey Raymond, 2025. "Generative AI at Work," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 140(2), pages 889-942.
    20. Harrison Hong & Jeffrey D. Kubik, 2003. "Analyzing the Analysts: Career Concerns and Biased Earnings Forecasts," Journal of Finance, American Finance Association, vol. 58(1), pages 313-351, February.
    21. Yuri Alexeev & Marwa H. Farag & Taylor L. Patti & Mark E. Wolf & Natalia Ares & Alán Aspuru-Guzik & Simon C. Benjamin & Zhenyu Cai & Shuxiang Cao & Christopher Chamberland & Zohim Chandani & Federico , 2025. "Artificial intelligence for quantum computing," Nature Communications, Nature, vol. 16(1), pages 1-19, December.
    22. Haowen Tian & Junkai Wang & Yue Cai, 2025. "Artificial Intelligence Adoption and Corporate ESG Performance," Business Strategy and the Environment, Wiley Blackwell, vol. 34(7), pages 8922-8945, November.
    23. Gus De Franco & Ole†Kristian Hope & Dushyantkumar Vyas & Yibin Zhou, 2015. "Analyst Report Readability," Contemporary Accounting Research, John Wiley & Sons, vol. 32(1), pages 76-104, March.
    24. Sufi R. Ahmed & Reza Baghdadi & Mikhail Bernadskiy & Nate Bowman & Ryan Braid & Jim Carr & Chen Chen & Pietro Ciccarella & Matthew Cole & John Cooke & Kishor Desai & Carlos Dorta & Jonathan Elmhurst &, 2025. "Universal photonic artificial intelligence acceleration," Nature, Nature, vol. 640(8058), pages 368-374, April.
    25. Alexander Bick & Adam Blandin & David Deming, 2023. "The Rapid Adoption of Generative AI," On the Economy 98843, Federal Reserve Bank of St. Louis.
    26. Bertomeu, Jeremy & Lin, Yupeng & Liu, Yibin & Ni, Zhenghui, 2025. "The impact of generative AI on information processing: Evidence from the ban of ChatGPT in Italy," Journal of Accounting and Economics, Elsevier, vol. 80(1).
    27. Jacob, John & Lys, Thomas Z. & Neale, Margaret A., 1999. "Expertise in forecasting performance of security analysts," Journal of Accounting and Economics, Elsevier, vol. 28(1), pages 51-82, November.
    28. Shihao Gu & Bryan Kelly & Dacheng Xiu, 2020. "Empirical Asset Pricing via Machine Learning," The Review of Financial Studies, Society for Financial Studies, vol. 33(5), pages 2223-2273.
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