ARTIFICIAL INTELLIGENCE ADOPTION IN ACCOUNTING: A THEORETICALL EXAMINATION OF OPPORTUNITIES, CHALLENGES AND IMPLICATION FOR THE FUTURE OF PROFESSIONAL ACCOUNTING PRACTICE

Abstract

Artificial Intelligence (AI) is being adopted across the accounting profession at a pace that has outrun the profession's theoretical understanding of what that adoption actually involves. Much of the existing literature treats AI adoption as a technical event — a system installed, a tool switched on — rather than as the organizational and professional process it actually is. This paper offers a theoretical examination of that process, integrating adoption theory (the Technology–Organization–Environment framework, the Technology Acceptance Model, and the Unified Theory of Acceptance and Use of Technology) with recent empirical evidence from accounting, auditing, and professional services research. It argues that AI adoption in accounting should be understood as a socio-technical process operating simultaneously at three levels — organizational readiness, individual acceptance, and professional identity — each of which can independently stall adoption regardless of a technology's capability. The paper reviews the opportunities AI creates across audit quality, fraud detection, predictive analytics, and advisory work, and sets these against the governance, ethical, and workforce challenges that recent field evidence shows are just as consequential. It closes by considering what sustained AI adoption implies for the accountant's professional role, for accounting education, and for the standard-setting bodies that will eventually have to formalize expectations around AI-assisted professional judgement. The contribution is a theoretical account of adoption that treats capability and acceptance as genuinely separate problems, neither of which rersolves the other.