Reconstructing Traditional Accounting Theory in the Era of Artificial Intelligence, Machine Learning, and the Internet of Things

Abstract

This article develops a conceptual-theoretical reconstruction of the traditional vision of accounting theory in response to the rise of Artificial Intelligence (AI), Machine Learning (ML), and the Internet of Things (IoT). Classical accounting theory built around principles of representation, verification, stewardship, conservatism, and periodicity is increasingly strained by the epistemic, ontological, and methodological consequences of technologies that generate real-time data, autonomous judgments, predictive computations, and algorithmic decision structures. This paper argues that AI and ML do not merely change the tools of accounting practice; they fundamentally challenge the assumptions about how accounting knowledge is produced, validated, and interpreted. IoT, as a pervasive data-generation infrastructure, further shifts accounting from an ex-post representation system to an ex-ante predictive ecosystem. Through conceptual analysis grounded in contemporary literature in accounting theory, information systems, and computational epistemology, this paper proposes a reconstructed theoretical model AI-Augmented Accounting Theory (A3T), which articulates new assumptions of ontology, epistemology, and methodology required for an AI-intensive accounting environment. The study contributes a clarifying framework for scholars attempting to reinterpret normative and positive theories of accounting under conditions of automation, autonomy, and real-time measurement, and outlines a comprehensive future research agenda for reconciling human judgment, algorithmic governance, predictive reporting, accounting ethics, auditability, and accountability.

Keywords: Accounting theory, AI, machine learning, IoT, epistemology, ontology, conceptual framework, prediction, automation, digital accounting.