Strategic cost management with AI-powered procurement simulationPROCUREMENT | CASE STUDY Agilent Technologies Challenge Solution Impact Agilent Technologies, a global leader in life sciences, diagnostics and applied chemical analysis, faced procurement inefficiencies from volatile supplier pricing, limited negotiation insights and manual processes, constraining cost optimization and proactive decision-making.Agilent implemented an AI-powered procurement intelligence solution combining machine learning, supply- market sentiment analysis and predictive analytics. The platform simulates negotiation scenarios, forecasts price movements and automates cost tracking. Advanced dashboards provide end-to-end visibility, enabling data-driven negotiations, proactive supplier engagement and faster response to market fluctuations.The solution strengthened procurement decision-making by embedding AI- driven negotiation intelligence, improving cost control, speed and resilience in volatile markets, delivering: –83% supplier should-cost* target achievement (up from 49%). –90% reduction in negotiation preparation time. –$10 million+ cumulative savings over two years. In today’s volatile supply chain, speed to decision and execution are critical. By embedding AI-driven intelligence across procurement and manufacturing, we enable accurate, fact-based decisions at scale driving cost discipline, resilience and faster responses to market dynamics for customers. Chow Woai Sheng, Vice President, Manufacturing, Global Operations, Agilent TechnologiesNote: *Should-cost is a data-driven estimate of a product’s fair cost, based on underlying cost drivers rather than the supplier’s quoted price. 3.2 Manufacturing engineering Manufacturing engineering today is anchored in static design, disconnected tools and one-time commissioning, leading to slow change cycles and growing gaps between design intent and shop-floor reality. The future is cognitive manufacturing engineering – where factories actively learn and improve from real-time data and co-create across ecosystems, turning engineering into a continuous, adaptive lifecycle that accelerates innovation, resilience and sustainability at scale. Intelligent Industrial Operations Outlook 2026 30