AI-Driven Quality Management in SAP S/4HANA for GMP- Regulated Industries

The pharmaceutical, biotechnology, and medical device industries operate under stringent Good Manufacturing Practice (GMP) regulations that mandate rigorous quality management processes across production, supply chain, and post-market surveillance. SAP S/4HANA, as the leading enterprise resource planning platform for regulated industries, provides an integrated foundation for quality management. However, the increasing complexity of global supply chains, the rising volume of quality events, and the accelerating pace of regulatory change have created demands that traditional rule-based quality systems are no longer equipped to satisfy. This study examined how artificial intelligence capabilities, including machine learning, natural language processing, predictive analytics, and computer vision, are being integrated within SAP S/4HANA Quality Management to address these demands. Drawing on a structured review of SAP technical documentation, regulatory frameworks including 21 CFR Part 11, EU GMP Annex 11, and ICH Q10, and published academic and practitioner research, this paper analyzed the architecture, mechanisms, and governance implications of AI augmented quality management in GMP-regulated environments. The findings indicate that AI integration within SAP QM enables significant improvements in defect prediction, non-conformance root cause analysis, audit readiness, and inspection planning efficiency. However, meaningful challenges persist in model validation, algorithmic transparency, change control for AI-modified processes, and regulatory acceptance of AI-generated quality decisions. A Layered AI Quality Governance Framework (LAQGF) is proposed to provide organizations with a structured approach to deploying AI-augmented quality management in compliance with applicable GMP requirements.