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The impact of generative AI on information processing: Evidence from the ban of ChatGPT in Italy

Author

Listed:
  • Bertomeu, Jeremy
  • Lin, Yupeng
  • Liu, Yibin
  • Ni, Zhenghui

Abstract

This paper explores how the emergence of generative artificial intelligence is reshaping the information environment in capital markets. Leveraging an unexpected ban on ChatGPT in Italy, we examine its impact on the information processing capabilities of market participants. We employ metrics for AI-generated text detection to show that the ban coincides with decreased AI usage by domestic financial analysts and fewer earnings forecasts issued relative to foreign analysts covering the same firm. The negative effects are more pronounced among analysts whose pre-ban reports are more consistent with AI use or analysts with a technical background. The ban also diminishes forecast accuracy, increases reliance on industry-specific information, and reduces information efficiency. Furthermore, investor reactions to earnings announcements become more pronounced, and bid–ask spreads widen, reflecting lower market efficiency.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:jaecon:v:80:y:2025:i:1:s0165410125000187
    DOI: 10.1016/j.jacceco.2025.101782
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    as
    1. Womack, Kent L, 1996. "Do Brokerage Analysts' Recommendations Have Investment Value?," Journal of Finance, American Finance Association, vol. 51(1), pages 137-167, March.
    2. Kothari, S. P., 2001. "Capital markets research in accounting," Journal of Accounting and Economics, Elsevier, vol. 31(1-3), pages 105-231, September.
    3. Aghamolla, Cyrus & Smith, Kevin, 2023. "Strategic complexity in disclosure," Journal of Accounting and Economics, Elsevier, vol. 76(2).
    4. Peng, Lin, 2005. "Learning with Information Capacity Constraints," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 40(2), pages 307-329, June.
    5. Blankespoor, Elizabeth & deHaan, Ed & Marinovic, Iván, 2020. "Disclosure processing costs, investors’ information choice, and equity market outcomes: A review," Journal of Accounting and Economics, Elsevier, vol. 70(2).
    6. repec:osf:socarx:v3cgs_v1 is not listed on IDEAS
    7. Richard Frankel & Jared Jennings & Joshua Lee, 2022. "Disclosure Sentiment: Machine Learning vs. Dictionary Methods," Management Science, INFORMS, vol. 68(7), pages 5514-5532, July.
    8. Matthias Breuer & Ed Dehaan, 2024. "Using and Interpreting Fixed Effects Models," Journal of Accounting Research, John Wiley & Sons, Ltd., vol. 62(4), pages 1183-1226, September.
    9. Glosten, Lawrence R. & Milgrom, Paul R., 1985. "Bid, ask and transaction prices in a specialist market with heterogeneously informed traders," Journal of Financial Economics, Elsevier, vol. 14(1), pages 71-100, March.
    10. Grossman, Sanford J & Stiglitz, Joseph E, 1980. "On the Impossibility of Informationally Efficient Markets," American Economic Review, American Economic Association, vol. 70(3), pages 393-408, June.
    11. Shuaiyu Chen & T. Clifton Green & Huseyin Gulen & Dexin Zhou, 2024. "What Does ChatGPT Make of Historical Stock Returns? Extrapolation and Miscalibration in LLM Stock Return Forecasts," Papers 2409.11540, arXiv.org.
    12. Joshua Livnat & Richard R. Mendenhall, 2006. "Comparing the Post–Earnings Announcement Drift for Surprises Calculated from Analyst and Time Series Forecasts," Journal of Accounting Research, John Wiley & Sons, Ltd., vol. 44(1), pages 177-205, March.
    13. Li, Feng, 2008. "Annual report readability, current earnings, and earnings persistence," Journal of Accounting and Economics, Elsevier, vol. 45(2-3), pages 221-247, August.
    14. Leland Bybee, 2023. "Surveying Generative AI's Economic Expectations," Papers 2305.02823, arXiv.org, revised May 2023.
    15. Peng, Lin & Xiong, Wei, 2006. "Investor attention, overconfidence and category learning," Journal of Financial Economics, Elsevier, vol. 80(3), pages 563-602, June.
    16. Elizabeth Blankespoor & Brian P. Miller & Hal D. White, 2014. "Initial evidence on the market impact of the XBRL mandate," Review of Accounting Studies, Springer, vol. 19(4), pages 1468-1503, December.
    17. Verrecchia, Robert E, 1982. "Information Acquisition in a Noisy Rational Expectations Economy," Econometrica, Econometric Society, vol. 50(6), pages 1415-1430, November.
    18. Kreitmeir, David & Raschky, Paul Anton, 2023. "The Unintended Consequences of Censoring Digital Technology - Evidence from Italy's ChatGPT Ban," SocArXiv v3cgs, Center for Open Science.
    19. S.P. Kothari & Eric So & Rodrigo Verdi, 2016. "Analysts’ Forecasts and Asset Pricing: A Survey," Annual Review of Financial Economics, Annual Reviews, vol. 8(1), pages 197-219, October.
    20. Laura L. Veldkamp, 2006. "Information Markets and the Comovement of Asset Prices," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 73(3), pages 823-845.
    21. Elizabeth Blankespoor & Ed Dehaan & John Wertz & Christina Zhu, 2019. "Why Do Individual Investors Disregard Accounting Information? The Roles of Information Awareness and Acquisition Costs," Journal of Accounting Research, John Wiley & Sons, Ltd., vol. 57(1), pages 53-84, March.
    22. Kai Li & Feng Mai & Rui Shen & Xinyan Yan, 2021. "Measuring Corporate Culture Using Machine Learning," NBER Chapters, in: Big Data: Long-Term Implications for Financial Markets and Firms, pages 3265-3315, National Bureau of Economic Research, Inc.
    23. Bryan Kelly & Alexander Ljungqvist, 2012. "Testing Asymmetric-Information Asset Pricing Models," The Review of Financial Studies, Society for Financial Studies, vol. 25(5), pages 1366-1413.
    24. Korinek, Anton, 2023. "Language Models and Cognitive Automation for Economic Research," CEPR Discussion Papers 17923, C.E.P.R. Discussion Papers.
    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. repec:bla:jfinan:v:59:y:2004:i:3:p:1083-1124 is not listed on IDEAS
    27. Daniel E. O'Leary, 2023. "An analysis of three chatbots: BlenderBot, ChatGPT and LaMDA," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 30(1), pages 41-54, January.
    28. Collins, Daniel W. & Kothari, S. P., 1989. "An analysis of intertemporal and cross-sectional determinants of earnings response coefficients," Journal of Accounting and Economics, Elsevier, vol. 11(2-3), pages 143-181, July.
    29. Kai Li & Feng Mai & Rui Shen & Xinyan Yan, 2021. "Measuring Corporate Culture Using Machine Learning [Machine learning methods that economists should know about]," The Review of Financial Studies, Society for Financial Studies, vol. 34(7), pages 3265-3315.
    30. Sims, Christopher A., 2003. "Implications of rational inattention," Journal of Monetary Economics, Elsevier, vol. 50(3), pages 665-690, April.
    31. Kyle, Albert S, 1985. "Continuous Auctions and Insider Trading," Econometrica, Econometric Society, vol. 53(6), pages 1315-1335, November.
    32. Brandon Gipper & Christian Leuz & Mark Maffett, 2020. "Public Oversight and Reporting Credibility: Evidence from the PCAOB Audit Inspection Regime," The Review of Financial Studies, Society for Financial Studies, vol. 33(10), pages 4532-4579.
    33. Dong, Yi & Li, Oliver Zhen & Lin, Yupeng & Ni, Chenkai, 2016. "Does Information-Processing Cost Affect Firm-Specific Information Acquisition? Evidence from XBRL Adoption," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 51(2), pages 435-462, April.
    34. Wood, David A. & Achhpilia, Muskan P. & Adams, Mollie T. & Aghazadeh, Sanaz & Akinyele, Kazeem & Akpan, Mfon & Allee, Kristian D. & Allen, Abigail M. & Almer, Elizabeth D. & Ames, Daniel & Arity, Vikt, 2023. "The ChatGPT artificial intelligence chatbot: How well does it answer accounting assessment questions?," Other publications TiSEM b4a29b3e-18a1-4259-a70c-d, Tilburg University, School of Economics and Management.
    35. Back, Kerry, 1992. "Insider Trading in Continuous Time," The Review of Financial Studies, Society for Financial Studies, vol. 5(3), pages 387-409.
    36. Ray Ball & Lakshmanan Shivakumar, 2008. "How Much New Information Is There in Earnings?," Journal of Accounting Research, John Wiley & Sons, Ltd., vol. 46(5), pages 975-1016, December.
    37. Chin‐Han Chiang & Wei Dai & Jianqing Fan & Harrison Hong & Jun Tu, 2019. "Robust Measures of Earnings Surprises," Journal of Finance, American Finance Association, vol. 74(2), pages 943-983, April.
    38. Christopher A. Sims, 2006. "Rational Inattention: Beyond the Linear-Quadratic Case," American Economic Review, American Economic Association, vol. 96(2), pages 158-163, May.
    39. Healy, Paul M. & Palepu, Krishna G., 2001. "Information asymmetry, corporate disclosure, and the capital markets: A review of the empirical disclosure literature," Journal of Accounting and Economics, Elsevier, vol. 31(1-3), pages 405-440, September.
    40. Marc Eulerich & Aida Sanatizadeh & Hamid Vakilzadeh & David A. Wood, 2024. "Is it all hype? ChatGPT’s performance and disruptive potential in the accounting and auditing industries," Review of Accounting Studies, Springer, vol. 29(3), pages 2318-2349, September.
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    3. Junhui Jeff Cai & Xian Gu & Liugang Sheng & Mengjia Xia & Linda Zhao & Wu Zhu, 2025. "AI as "Co-founder": GenAI for Entrepreneurship," Papers 2512.06506, arXiv.org.
    4. Shuchen Meng & Xupeng Chen, 2026. "Artificial Intelligence and Systemic Risk: A Unified Model of Performative Prediction, Algorithmic Herding, and Cognitive Dependency in Financial Markets," Papers 2604.03272, arXiv.org.
    5. Stratopoulos, Theophanis C. & Wang, Victor Xiaoqi, 2025. "Artificial intelligence and accounting research: a framework and agenda," International Journal of Accounting Information Systems, Elsevier, vol. 56(C).
    6. Keil, Samuel & Martin, Pascal & Schiereck, Dirk, 2026. "Do Investors Trust in AI Investments of European Companies?," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 159306, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    7. Fu, Yu & Chen, Yijun & Zhang, Yulin & Wang, Menghan & Yu, Yuanchun, 2026. "Corporate productivity transformation under the innovation paradigm: The role and impact of artificial intelligence," Technology in Society, Elsevier, vol. 84(C).
    8. Jian Xue & Qian Zhang & Wu Zhu, 2025. "Generative AI for Analysts," Papers 2512.19705, arXiv.org.
    9. Yang ZHANG & Ziang QIU Ziang & Donghyun PARK & Shu TIAN, 2026. "Role of Artificial Intelligence in Finance: Selective Literature Review and Implications for Asia's Financial Stability," Working Papers wp61, South East Asian Central Banks (SEACEN) Research and Training Centre, revised Feb 2026.

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    JEL classification:

    • O00 - Economic Development, Innovation, Technological Change, and Growth - - General - - - General
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • O38 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Government Policy
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • E65 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook - - - Studies of Particular Policy Episodes
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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