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Determinants of artificial intelligence adoption in audit firms: an immersion in theoretical approaches and a proposed conceptual framework
Asmae Ez-Zaidi, Youssef Ghandari

Determinants of artificial intelligence adoption in audit firms: an immersion in theoretical approaches and a proposed conceptual framework

Author / Organization:
Science & Mathematics Published 2026 Verification Pending

Overview & Synopsis

With the rapid rise of artificial intelligence (AI), organizations are racing to leverage its benefits, prompting research into the factors influencing its adoption. This article explores the determinants of AI adoption in audit firms using an integrated model combining the TOE framework, Diffusion of Innovations (DOI) theory, and institutional theory. It aims to identify both drivers and barriers shaping decisions to implement AI, considering technological, organizational, and environmental contexts. Technologically, DOI highlights factors such as complexity, compatibility, and relative advantage. Organizationally, the TOE framework emphasizes firm size, management support, and readiness. Externally, institutional theory explains pressures from competition, regulation, and professional expectations. By integrating these perspectives, the study provides a comprehensive understanding of AI adoption in audit firms and establishes a strong conceptual basis for future empirical research.

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Document Information

Document Title Determinants of artificial intelligence adoption in audit firms: an immersion in theoretical approaches and a proposed conceptual framework
Author / Organization Asmae Ez-Zaidi, Youssef Ghandari
Subject & Discipline Multidisciplinary Academic Open Research
Categories Science & Mathematics
Publication Year 2026
License / Rights Open Access / Creative Commons
Resource Verification Listed PDF (Verification Pending)
Original Host Website HAL Open Science (hal.science)
File Format application/pdf (Portable Document Format)
Language EN
Catalog ID DOC-97284
Original Source Link Visit Source Page on hal.science »