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Toward artificial governance? The role of artificial intelligence in shaping the future of corporate governance

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  • Michael Hilb

    (University of Fribourg)

Abstract

The article explores the impact of the ongoing progress and adaptation of artificial intelligence on the practice of the corporate governance. It applies three lenses to artificial governance—the business, technology and society lenses—to assess the desirability, feasibility and responsibility of automating board-level decision-making to ensure effective corporate governance. Based on an assessment of the potential and limitations of human and machine learning for effective board-level decision-making, the article proposes five scenarios of artificial governance, i.e. assisted, augmented, amplified, autonomous and autopoietic intelligence, that are likely to shape the governance of organizations today, tomorrow and beyond. It discusses the implications of both the governance of and the governance with artificial intelligence in the three horizons and concludes with an appeal to board members to take an active role in understanding, imagining and shaping the future of artificial governance.

Suggested Citation

  • Michael Hilb, 2020. "Toward artificial governance? The role of artificial intelligence in shaping the future of corporate governance," Journal of Management & Governance, Springer;Accademia Italiana di Economia Aziendale (AIDEA), vol. 24(4), pages 851-870, December.
    • Handle: RePEc:kap:jmgtgv:v:24:y:2020:i:4:d:10.1007_s10997-020-09519-9
    DOI: 10.1007/s10997-020-09519-9
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    Citations

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    Cited by:

    1. Nam, Jinyoung & Jung, Yoonhyuk & Kim, Junghwan, 2024. "Understandings of the AI business ecosystem in South Korea: AI startups’ perspective," Telecommunications Policy, Elsevier, vol. 48(6).
    2. Oliveira, Fabio & Kakabadse, Nada & Khan, Nadeem, 2022. "Board engagement with digital technologies: A resource dependence framework," Journal of Business Research, Elsevier, vol. 139(C), pages 804-818.
    3. Zhou, Zhongsheng & Li, Zhuo & Du, Shanzhong & Cao, June, 2024. "Robot adoption and enterprise R&D manipulation: Evidence from China," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
    4. Dangxing Chen & Luyao Zhang, 2023. "Monotonicity for AI ethics and society: An empirical study of the monotonic neural additive model in criminology, education, health care, and finance," Papers 2301.07060, arXiv.org.
    5. Mehtap A. Eklund, 2021. "The COVID-19 lessons learned for business and governance," SN Business & Economics, Springer, vol. 1(1), pages 1-11, January.
    6. Manal Ahdadou & Abdellah Aajly & Mohamed Tahrouch, 2024. "Unlocking the potential of augmented intelligence: a discussion on its role in boardroom decision-making," International Journal of Disclosure and Governance, Palgrave Macmillan, vol. 21(3), pages 433-446, September.
    7. Adrian GROȘANU & Melinda-Timea FÜLÖP & Nicolae MĂGDAȘ, 2024. "Ethical Dilemmas in Digital Accounting: A Comprehensive Literature Review," CECCAR Business Review, Body of Expert and Licensed Accountants of Romania (CECCAR), vol. 5(4), pages 56-67, April.
    8. Mu, Rui & Haershan, Maidina & Wu, Peiyi, 2022. "What organizational conditions, in combination, drive technology enactment in government-led smart city projects?," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
    9. Nam, Jinyoung & Kim, Junghwan & Jung, Yoonhyuk, 2023. "Understandings of the AI business ecosystem in South Korea: AI startups' perspective," 32nd European Regional ITS Conference, Madrid 2023: Realising the digital decade in the European Union – Easier said than done? 278005, International Telecommunications Society (ITS).

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