Integrating Artificial Intelligence and Enterprise Resource Planning Systems: A Structured Review of Decision Support Capabilities, Constraints, and Governance

Abdullah Önden

doi:10.31181/msa31202643

Authors

Abdullah Önden Department of Computer Engineering, Istanbul University, Faculty of Computer and Information Technologies, Istanbul, Türkiye Author https://orcid.org/0000-0003-3769-8193

DOI:

https://doi.org/10.31181/msa31202643

Keywords:

Literature Review, Artificial Intelligence, Enterprise Resource Planning, Management Decisions, Decision Support Systems, Machine Learning, Predictive Analytics, Business Intelligence

Abstract

This review paper examines the integration of artificial intelligence (AI) into enterprise resource planning (ERP) systems to support real-time, evidence-based decision-making across core business functions. The study draws on a structured review of peer-reviewed and standards-based sources published between 2020 and 2025. It considers how AI techniques, including machine learning, predictive analytics, anomaly detection, and explainable AI, enhance ERP-enabled planning, control, and performance management in finance, procurement, manufacturing, and supply chain operations. The review identifies enabling conditions for value realization, such as data governance, process standardization, and change management, as well as constraints related to model risk, bias, privacy, and organizational readiness. Management findings are interpreted through socio-technical systems and resource-based perspectives, with emphasis on the point that durable benefits depend on the co-evolution of technology, people, and process capabilities.

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