英文【GEP】面向采购专业人士的代理人工智能手册

1THE AGENTIC AIPLAYBOOK FORPROCUREMENT PROSHow to Move from Hype to Action and Results2The last three years have redrawn the boundaries of what’s possible in procurement. Generative AI came first, showing that machines could now write, sum-marize and converse in ways that felt natural. But the value was narrow. Writing supplier emails faster didn’t make the sourcing cycle shorter.Then came AI agents. These tools promised task-level automation. An agent could complete an RFQ, update a supplier record or respond to routine queries. Helpful, yes. But still reactive — dependent on instructions, limited in scope and easily derailed by exceptions.What we’re seeing now is qualitatively different.Agentic AI systems don’t just wait for tasks. They in-terpret goals, build plans, weigh trade-offs, and then act. They can understand a category strategy, detect when it’s no longer working, and recommend a shift, with supporting data. Unlike earlier tools, these systems don’t just com-plete tasks. They orchestrate decisions across sys-tems and teams, working toward defined outcomes with minimal handholding. This is not just another evolution in AI capabilities. It’s a shift in how enter-prise systems operate.“90% of CPO survey respondents say they have considered or are considering using AI agents to optimize their procurement operations in the next 6 to 12 months.”1AI is Moving Fast, And So Must Procurement3Three fundamental developments enabled this shift, with each one accelerating the next.While early LLMs were impressive in language gen-eration, they were weak in enterprise reasoning. That changed as models began ingesting multimodal data — from invoices and contracts to market indices and supplier risk reports. Today’s models can parse the fine print in a force majeure clause, recognize patterns in invoice anomalies or extract supplier risk from external financial data.Earlier agents were designed to follow workflows. They could complete predefined steps but lacked adaptability. Today’s agentic systems can pursue a goal, such as “identify cost-saving opportunities in indirect categories over the next quarter,” and work toward it by exploring data, orchestrating workflows, and engaging users only when needed.Procurement teams face a wide range of challenges — from tariffs and supply disruptions to ESG man-dates and shifting regulations. They must navigate complexity across global markets while collaborating more closely with finance, legal and sustainability teams. Static playbooks and reactive processes are no longer enough.Agentic AI arrives at a time when procurement needs systems that can adapt in real time and take the lead when conditions shift.What Changed?Foundation models became operational12AI agents gained autonomy3Procurement’s role became broader and more exposed4Most procurement technology today still runs on fixed rules and triggers. A system detects that a purchase order (PO) exceeds $50,000 and routes it for managerial approval. A three-bi