Transforming Accounting Theory through the Application of Artificial Intelligence (AI), Machine Learning (ML), and the Internet of Things (IoT): Approaches to Business Model Innovation, Risk Management, and Financial Prediction

Abstract

The integration of Artificial Intelligence (AI), Machine Learning (ML), and the Internet of Things (IoT) into accounting practices is revolutionizing traditional frameworks, offering new opportunities for business model innovation, enhanced risk management, and improved financial prediction. This paper explores the intersection of these emerging technologies with accounting theory, examining their transformative impact on financial reporting, auditing, and decision-making processes. AI and ML algorithms enable more accurate forecasting, anomaly detection, and automated decision-making, while IoT technologies facilitate real-time data collection and analysis, creating new avenues for operational efficiency and predictive capabilities. Despite these advancements, challenges such as the "black-box" nature of AI, the need for interpretability, and the integration of these technologies into existing systems remain. This study provides a comprehensive framework for understanding how these technologies reshape accounting practices, proposing theoretical models and strategies to address these challenges. The paper also highlights future research opportunities, emphasizing the need for accounting scholars to explore the theoretical implications of AI, ML, and IoT, and to collaborate with interdisciplinary teams to fully leverage the potential of these technologies in the accounting field. This abstract highlights the key themes of business model innovation, risk management, and financial prediction, and introduces a theoretical perspective on how these technologies are reshaping accounting practices.