AI-powered accounting: Analysing accuracy and efficiency using machine learning algorithms and predictive models

With each passing day, AI and ML continue to revolutionize the world of industry. For that reason, accounting too cannot stay behind. The ever-evolving technologies of artificial intelligence and machine learning are being widely applied to automate regular activities, reduce human error, and ensure better precision in financial reporting by deploying AI accounting systems. Recent AI-based accounting systems apply advanced machine learning algorithms to transaction classification, error detection, and financial trend predictions instead of manual accounting practices. This paper has evaluated accuracy, development in efficiency, and anomaly detection while assessing the performance of AI compared to conventional manual practices of accounting systems. This work seeks to find out how AI-human interfaces, machine learning models that include some supervised learning algorithms, predictive analytics, and clustering techniques, can significantly enhance financial reporting reliability while simplifying accounting processes. The survey results also show that AI-driven systems provide higher levels of accuracy and faster speed, and may also offer superior mechanisms for identifying anomalies in financial information. These insights underscore the transformative potential of AI in accounting: AI will undoubtedly be crucial in advancing both operational efficiencies and financial decisions.