Artificial Intelligence in Accounting Business 2.0: An Empirical Study using Structural Equation Modeling

Artificial Intelligence in Accounting Business 2.0: An Empirical Study using Structural Equation Modeling Dr. Shivganga C. Maindargi Assistant Professor, Management Studies, Bharati Vidyapeeth (Deemed to be) University, Pune Dr. Rahul Manjare Assistant Professor, Management Studies, Bharati Vidyapeeth (Deemed to be) University, Pune Dr. Shabnam Mahat (Mane) Assistant Professor, Management Studies, Bharati Vidyapeeth (Deemed to be) University, Pune Abstract Technology has revolutionized the process, policies and ways of doing businesses. Artificial Intelligence (AI) is fundamentally transforming accounting practices by shifting the discipline from manual, compliance-driven record keeping toward intelligent, automated, and analytics-oriented systems often referred to as Accounting Business 2.0. AI technologies such as machine learning, robotic process automation (RPA), and natural language processing are increasingly embedded in bookkeeping, auditing, financial reporting, and decision-support systems. The present study investigates the implications of AI adoption on accounting efficiency, audit quality, managerial decision support, and professional skill requirements. A mixed-method explanatory research design was adopted using survey data collected from 182 accounting and finance professionals along with supporting industry case evidence. Statistical techniques including reliability testing, correlation analysis, multiple regression, and Structural Equation Modeling (SEM) were applied. The results indicate significant positive relationships between AI adoption and accounting efficiency (β = .56), audit quality (β = .48), and decision support capability (β = .51). The findings suggest that AI-enabled accounting systems enhance performance outcomes while simultaneously increasing demand for analytical and technological competencies. The study concludes that AI adoption is a strategic necessity for modern accounting systems, though governance and ethical controls remain essential. Keywords: Artificial Intelligence, Accounting Automation, Accounting Business 2.0, RPA, Machine Learning, Audit Analytics, SEM