Abstract

The life sciences industry is subject to strict regulations, and procurement must be efficient and low-cost and comply with international safety and quality standards. This article presents an innovative framework integrating Artificial Intelligence (AI) and SAP Ariba to revolutionize procurement operations in the life sciences sector, with a particular focus on predictive compliance and risk control. Now we introduce a procurement architecture driven by AI that uses machine learning algorithms, natural language processing and advanced analytics to generate within the SAP Ariba system risk scores automatically, consolidate knowledge on supplier qualification, ensure not only reactive but also proactive compliance with Good Manufacturing Practices (GMP), GxP, and emerging international regulations. The framework affords real-time anomaly detection, supplier risk detection and dynamic supplier assessments. All these contribute to the control of regulatory and operational risks in every link within supply chains. Drawing on case studies from life sciences businesses worldwide, this intelligent procurement model shows how decisions made with a knowledge-based approach produce results that accelerate supply cycle times and reduce disruption risks. The paper also suggests ways to integrate AI modules into SAP Ariba workflows, best practices from hands-on experiences in complex projects, and the implications for procurement leaders who want resilient, transparent and compliant supply chains. In mainstreaming these two approaches, the study offers a standard architecture for AI and procurement systems in the life sciences.

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