The pharmaceutical supply chain confronts mounting exposure from vendor weaknesses, counterfeit products, lapses in regulatory conformance, and escalating cyber aggressions, all of which threaten patient safety and erode operational resilience. Conventional vendor risk management tactics function satisfactorily within transactional silos yet falter against the intersecting, fluid compliance demands of life sciences. This study advances an AI-augmented vendor risk governance apparatus, fused with SAP Ariba, precisely to fortify pharmaceutical procurement. By situating cutting-edge artificial intelligence modalities, natural language processing, anomaly detection, and predictive analytics within the SAP Ariba procurement architecture, the proposal cultivates forward-looking detection of elevated-suspicion suppliers, continuous compliance telemetry, and automated, intelligent execution of all relevant diligence workflows. A conceptual case vignette narrates how pharmaceutical companies can concretely operationalize the architecture, reporting notable uplifts in vendor choice, diminished supply interruption, and firmer observance of global regulatory regimes, including FDA, EMA, and GDPR demands. Hence, the principal scholarly advance resides in furnishing stakeholders with a scalable, evidence-driven, and dynamically adaptive vendor oversight configuration that simultaneously elevates supply chain integrity, lays the foundational stone for predictive compliance, and cultivates resilience in pharmaceutical sourcing activities.