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@article{183418,
        author = {Sandeep Shenoy Karanchery Sundaresan},
        title = {AI-Powered Data Analytics in ERP: Revolutionizing Supply Chain Decision-Making in Healthcare},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {3},
        pages = {1628-1637},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=183418},
        abstract = {The integration of Artificial Intelligence (AI) into Enterprise Resource Planning (ERP) systems is revolutionizing healthcare supply chain management by enabling predictive, real-time, and automated decision-making. This review synthesizes academic and industry research on the role of AI-powered analytics in ERP platforms, particularly their application to forecasting, procurement, compliance monitoring, and operational optimization within healthcare settings. By examining empirical case studies, theoretical frameworks, and simulation data, the study identifies measurable benefits such as increased forecast accuracy, reduced lead times, and fewer stockouts. However, challenges persist in terms of data integration, ethical governance, and system interoperability. The article concludes with strategic future directions for research and implementation aimed at enhancing the reliability and scalability of AI-ERP solutions for smarter, more resilient healthcare supply chains.},
        keywords = {AI in ERP, Healthcare Supply Chain, Predictive Analytics, Compliance, Forecasting, Digital Transformation, Inventory Optimization, Machine Learning, Smart Procurement, Real-Time Decision Support},
        month = {August},
        }