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Theorization of Institutional Change in the Rise of Artificial Intelligence

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  • Masashi Goto

    (Research Institute for Economics and Business Administration, Kobe University, JAPAN)

Abstract

This study explores how professional institutional change is theorized in the context of the emergence of disruptive technology as a precipitating jolt. I conducted a case study of two Big four accounting firms in Japan on their initiatives to apply artificial intelligence (AI) to their core audit services between 2015 and 2017. The data shows the process for incumbent dominant organizations to collaborate and develop social perceptions about the changing but continuing relevance of their profession. The analysis suggests that the retheorization can advance even without concrete alternative templates when disruptive technology is perceived to have overwhelming influences, following multi-level steps progressing from internal to external theorization. This article proposes a grounded theory model of the process of professional institutional change: (1) Theorizing change internally at the field, (2) Developing solutions by experimentations in organizations, (3) Exploring solutions driven by individuals in organizations and (4) Theorizing change externally by organizations. It contributes to the profession and institutional scholarship by expanding our knowledge about the diversity of professional institutional field change process in this age of increasing technology influences on organizations.

Suggested Citation

  • Masashi Goto, 2020. "Theorization of Institutional Change in the Rise of Artificial Intelligence," Discussion Paper Series DP2020-12, Research Institute for Economics & Business Administration, Kobe University.
  • Handle: RePEc:kob:dpaper:dp2020-12
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    File URL: https://www.rieb.kobe-u.ac.jp/academic/ra/dp/English/DP2020-12.pdf
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    References listed on IDEAS

    as
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    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Institutional change; Professions; Artificial intelligence; Qualitative research; Grounded theory;
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