AI-Driven Supply Chain Optimization and Zero-Touch Workforce Management in Pediatric Healthcare: A Privacy-Preserving Framework Using Natural Language Processing and SAP

Abstract

The integration of Artificial Intelligence (AI) with enterprise resource planning (ERP) systems such as SAP is transforming the way pediatric healthcare organizations manage their operational ecosystems. This paper presents a comprehensive, privacy-preserving AI framework designed to optimize the supply chain and enable zero-touch workforce management in pediatric healthcare environments. By leveraging Natural Language Processing (NLP), the proposed framework facilitates intelligent automation across procurement, inventory control, clinical logistics, and workforce scheduling processes. The system employs advanced predictive analytics to forecast demand for medical supplies, pharmaceuticals, and human resources, thereby minimizing shortages and inefficiencies. Through real-time insights from SAP S/4HANA and AI-driven data interpretation, the framework supports evidence-based decision-making and adaptive resource allocation. The zero-touch workforce management model eliminates repetitive administrative tasks by automating approval workflows, shift allocation, and compliance tracking, allowing healthcare professionals to focus more on patient care and less on operational overhead. A key contribution of this study is the implementation of privacy-preserving mechanisms, including federated learning, differential privacy, and homomorphic encryption, to ensure secure collaboration among hospitals, suppliers, and workforce management systems without sharing raw patient or institutional data. The use of NLP-based conversational agents further enhances communication efficiency among clinical and administrative teams by interpreting and responding to unstructured queries while maintaining data confidentiality. The proposed AI–SAP integration demonstrates significant potential to achieve operational resilience, cost reduction, and sustainable healthcare delivery in pediatric settings. Experimental evaluations and scenario-based simulations indicate measurable improvements in supply chain transparency, reduced workforce downtime, and enhanced regulatory compliance under frameworks such as HIPAA and GDPR. Ultimately, this research contributes to the ongoing digital transformation of pediatric healthcare by providing a scalable, intelligent, and secure model for AI-driven operational excellence.