INTEGRATING APPLIED AI WITH ENTERPRISE RESOURCE PLANNING SYSTEMS FOR INTELLIGENT MANUFACTURING DECISION SUPPORT IN SAUDI ARABIA

Artificial intelligence is increasingly used as a decision-making layer surrounding enterprise resource planning systems, although the evidence is still scattered throughout the areas of manufacturing analytics, digital twins, supply - chain intelligence and enterprise information systems. The present review looks at how applied artificial intelligence can be combined with ERP-based architectures in order to enhance intelligent decision support for manufacturing in Saudi Arabia. A selective integrative review draws on thirty peer - reviewed publications from 2020 to 2025 with verified bibliographic records. The corpus combines direct manufacturing evidence with contextual studies of ERP, technology adoption and decision governance. The evidence was categorised according to decision level, data source, integration method, AI capability, operational outcome and governance need. Official PMI guidance, outside the scholarly corpus, informs a CPMAI-based governance adaptation. The synthesis suggests that ERP can provide a foundation for AI when it serves as a governed enterprise context layer that links together finance, procurement, inventory, production and supply-chain records with data from manufacturing execution, the industrial Internet of Things and digital twins. Forecasting, scheduling, maintenance, quality, inventory and resilience decisions can then be supported through machine learning, explainable analytics and optimisation, on the condition that the results of the models are incorporated into accountable human workflows. For Saudi manufacturers, the review identifies potential constraints in data quality, interoperability, process ownership, cybersecurity, skills and decision governance.