International Journal For Multidisciplinary Research

E-ISSN: 2582-2160     Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Call for Paper Volume 6 Issue 6 November-December 2024 Submit your research before last 3 days of December to publish your research paper in the issue of November-December.

Synergizing Ai and ERP for Predictive Supply Chain Management and Quality Assurance in Healthcare

Author(s) Kamalendar Reddy Kotha, Sai Charan Tokachichu, Srikanth Padakanti
Country United States
Abstract This article explores the transformative potential of integrating Artificial Intelligence (AI) with Enterprise Resource Planning (ERP) systems in healthcare, focusing on applications in predictive supply chain management and quality assurance. The healthcare industry faces increasing pressure to improve efficiency while maintaining high-quality care, and AI-ERP integration offers a compelling solution. By combining ERP's comprehensive data management capabilities with AI's predictive and analytical power, healthcare organizations can enhance operational efficiency, improve decision-making, and ultimately deliver better patient outcomes. The article examines current implementations, case studies, and future projections to provide a comprehensive overview of how this technological synergy can help healthcare providers navigate the complex challenges of modern healthcare delivery, from optimizing inventory levels to ensuring regulatory compliance and proactive risk management.
Keywords Keywords: Artificial Intelligence, Enterprise Resource Planning, Healthcare Supply Chain, Predictive Analytics, Quality Assurance
Field Computer
Published In Volume 6, Issue 5, September-October 2024
Published On 2024-10-31
Cite This Synergizing Ai and ERP for Predictive Supply Chain Management and Quality Assurance in Healthcare - Kamalendar Reddy Kotha, Sai Charan Tokachichu, Srikanth Padakanti - IJFMR Volume 6, Issue 5, September-October 2024. DOI 10.36948/ijfmr.2024.v06i05.29762
DOI https://doi.org/10.36948/ijfmr.2024.v06i05.29762
Short DOI https://doi.org/g8p2rr

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