Year: 2025
Type: article
Abstract: The integration of artificial intelligence with Enterprise Resource Planning systems represents a transformative evolution in business process automation capabilities, addressing fundamental limitations of traditional implementations through intelligent, adaptive technologies. AI-powered ERP systems overcome conventional constraints including batch processing architectures, rigid workflows, and limited analytical capabilities by introducing real-time decision support, predictive modeling, and autonomous process execution. The convergence of machine learning, natural language processing, and robotic process automation delivers significant operational improvements across diverse industry sectors, with documented performance enhancements in forecast accuracy, process efficiency, cost reduction, and decision quality. Applications in dynamic inventory management, financial fraud detection, and predictive maintenance demonstrate how these capabilities address specific business challenges while delivering quantifiable returns. Despite implementation obstacles including data fragmentation, ethical considerations, and computational demands, organizations are developing effective strategies to realize the full potential of AI-ERP integration. Emerging technologies including edge computing, generative AI, and blockchain integration promise to further expand these capabilities, transforming enterprise systems from passive record-keeping platforms to proactive management tools that anticipate needs, identify risks, and optimize operations across organizational boundaries.
Author: Ramadevi Sannapureddy
Institution: Sikkim Manipal University
Language: English
Subfield: Management Information Systems
Domain: Social Sciences
Open Access status: hybrid
OpenAlex ID: W4411123034