面向采购专业人士的代理人工智能手册

Investment Rating - The report indicates a strong interest in adopting agentic AI in procurement, with 90% of Chief Procurement Officers (CPOs) considering its use within the next 6 to 12 months [3]. Core Insights - Agentic AI represents a significant evolution in procurement technology, moving from task automation to autonomous decision-making, enabling procurement teams to adapt in real-time to changing conditions [10][15]. - The report highlights that by 2028, 33% of enterprise software applications will incorporate agentic AI, a substantial increase from less than 1% in 2024, allowing for 15% of daily work decisions to be made autonomously [38]. Summary by Sections Evolution of AI in Procurement - The last three years have seen rapid advancements in AI capabilities, particularly with the introduction of agentic AI systems that can interpret goals and make decisions autonomously [2][4]. - Three key developments have facilitated this shift: operational foundation models, increased autonomy of AI agents, and the broader role of procurement teams facing complex challenges [6][9]. Capabilities of Agentic AI - Agentic AI systems differ from traditional procurement systems by incorporating planning, context awareness, collaboration, and learning capabilities, allowing them to act on defined objectives rather than following rigid workflows [14]. - The report outlines a comparison of capabilities across conventional systems, AI agents, and agentic AI, emphasizing the latter's ability to create strategies based on goals and data [14]. Use Cases - Autonomous Sourcing and Negotiation: Agentic AI can manage both high-volume low-value buys and high-value strategic sourcing, providing a seamless end-to-end digital sourcing layer that learns and improves over time [17][20]. - Intelligent Category Management: These systems continuously monitor category-level data and can adapt strategies in real-time, ensuring procurement remains agile in a fast-moving market [23][25]. - Real-Time Compliance: Agentic AI integrates structured and unstructured data to maintain a live view of compliance, enabling proactive rather than reactive management of regulatory changes [26][28]. Agentic AI Infrastructure - The report details the necessary components for effective agentic AI, including a multimodal AI core, procurement-tuned intelligence, super-agent orchestration, a connected data layer, and a governance framework [29][33]. - A unified source-to-pay platform is essential for maximizing the value of agentic AI, allowing for fluid data flow and complete visibility across procurement processes [34]. Strategic Focus for Procurement Leaders - Leaders are advised to set clear goals, identify high-impact use cases, understand their data landscape, and prepare teams to work alongside intelligent systems to leverage the full potential of agentic AI [40][44]. - The report emphasizes the importance of aligning organizational structures and incentives with business goals rather than just process compliance [49].