Traditional automation tools lack the agility and scalability to adapt to evolving operational needs.
This podcast, based on the GEP whitepaper "Agentic AI Buyer's Guide: How To Evaluate Enterprise-Ready Agentic AI for Procurement and Supply Chain," gives procurement leaders a framework to evaluate agentic AI platforms that reason, plan, and execute multi-step procurement workflows.
Learn how agentic orchestration interprets nuance and autonomously manages end-to-end processes, applying domain-specific intelligence to handle complex policy conflicts, supplier risks, and exceptions that rule-based automation cannot.
What's Inside:
- Distinguishing agentic AI from RPA, chatbots, and workflow engines.
- The three-layer architecture: assistant, orchestration, and extensibility.
- A maturity framework for evaluating autonomous orchestration levels.
Organizations that adopt this model move beyond reactive problem-solving toward intelligent, data-driven orchestration, achieving faster cycle times, better decisions, continuous optimization, and greater resilience during disruptions.
Listen to the podcast now.
FAQ
Traditional automation is rule-based and lacks the ability to interpret nuance or coordinate complex, end-to-end processes. In contrast, agentic AI uses domain-specific intelligence to reason, decide, and act autonomously. This allows the system to resolve exceptions and adapt to changing market conditions or supply disruptions without constant manual intervention.
Enterprise-ready platforms typically consist of three integrated layers: the assistant layer, the orchestration layer, and the extensibility layer. The assistant layer provides a conversational interface for user interaction, while the orchestration layer enables a network of agents to collaborate on multi-step tasks and system coordination. Finally, the extensibility layer allows teams to build or adapt agents for specific categories, regions, or evolving workflows.
The maturity framework defines three levels: Assisted Intelligence, Coordinated Intelligence, and Autonomous Orchestration, to help leaders distinguish between incremental improvements and true intelligence. Level 3 systems represent the highest maturity, where agents plan and act across multiple systems and functions within governed controls. This framework ensures buyers select platforms capable of delivering meaningful autonomy rather than just basic task support.