The Transformation and Sublimation of Accounting Information in the Wave of Digital Intelligence

Abstract

In the digital intelligence era, this study examines the AI and big data - driven automated accounting information processing model and its impact on information quality. Traditional accounting, relying on manual work, has low efficiency, high error rates, and information silos. AI and big data technologies automate data collection, improve processing efficiency, and enable real - time sharing. AI, with machine learning and deep - learning algorithms, automates tasks and reduces errors. Big data offers comprehensive resources for accounting analysis. Through the case of ABC Manufacturing Co., Ltd. and an empirical study of 100 enterprises, the research proves that these technologies significantly boost efficiency and quality. For ABC Company, data collection time drops by about 300 times, period - end closing time shortens by 80%, and financial statement generation time reduces by 98.6%. Empirical analysis shows AI application and big data maturity positively impact efficiency (up 65.3% - 82.7%) and accuracy (up 86.7%). Yet, risks like data security issues, algorithm bias, and skill shortages exist. Countermeasures include data encryption, quality data control in algorithm training, and personnel training. Overall, AI and big data integration is the future of accounting, driving deeper intelligence and data - based decision - making for industry development.