The Digital Transformation of Accounting Information Systems A Systematic Literature Review of Emerging Technologies, Organizational Capabilities, and Future Research Directions
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Abstract
The rapid advancement of emerging digital technologies including artificial intelligence (AI), blockchain, cloud computing, big data analytics, and robotic process automation (RPA) has fundamentally transformed accounting information systems (AIS). Despite growing interest in digital transformation within accounting, a comprehensive synthesis of how these technologies collectively impact AIS effectiveness, efficiency, and organizational capabilities remains limited. This systematic literature review addresses this gap by synthesizing empirical evidence on the digital transformation of AIS. Following PRISMA 2020 guidelines, a comprehensive search was conducted across eight database sources covering publications from 2016 to 2026. After removing 362 duplicates from 1,792 initial records, 500 relevance-ranked papers underwent title/abstract screening, yielding 117 papers for full-text assessment, which resulted in 103 included studies. The 103 included studies revealed that AI, blockchain, cloud computing, big data analytics, and RPA significantly enhance AIS effectiveness through improved accuracy (72–79% in predictive models), automation of routine tasks, real-time reporting capabilities, and enhanced transparency. Organizational capabilities required for successful adoption include technical skills development, robust governance frameworks, cultural readiness, and adequate technological infrastructure. Major implementation challenges include high costs, cybersecurity concerns, data privacy issues, skills gaps, and regulatory uncertainties. Digital transformation profoundly reshapes AIS by automating processes, enhancing decision-making quality, and improving financial reporting reliability. Successful implementation requires comprehensive organizational readiness, including workforce upskilling, governance frameworks, and strategic alignment. Future research should address geographical biases, explore ethical dimensions of AI adoption.
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