S&P Global and IBM Expand AI Use in Supply Chain Tools

• S&P Global integrates IBM’s watsonx Orchestrate to enhance supply chain visibility and decision-making with agentic AI technology.

AI Agents Enter the Supply Chain

S&P Global and IBM have announced a strategic partnership to embed IBM’s watsonx Orchestrate framework into S&P Global’s enterprise offerings. The collaboration begins with supply chain management, aiming to address persistent challenges in procurement and vendor selection. By combining S&P Global’s proprietary data with IBM’s agentic AI, the companies intend to improve visibility across trade, country, and supplier risk domains. This integration is expected to support faster, more informed decision-making for enterprise clients.

The initiative includes the development of new AI agents tailored to S&P Global’s datasets, which will be added to IBM’s watsonx Orchestrate Agent Catalog. These agents are designed to automate workflows and connect data insights directly to operational actions. S&P Global plans to extend the use of IBM’s AI technology beyond supply chain applications, incorporating it into broader risk intelligence services. The effort reflects a growing trend toward modular, agent-based AI systems in enterprise environments.

Expanding AI Capabilities Across Business Functions

Executives from both companies emphasized the practical benefits of the alliance. Saugata Saha of S&P Global highlighted the potential for AI to streamline workflows and improve procurement strategies. Rob Thomas of IBM noted that global supply chains have become increasingly complex, and agentic AI can help businesses regain control and optimize performance. The partnership is positioned as a scalable model, with future applications in finance, insurance, and other core business areas.

S&P Global’s supply chain tools are part of its Risk & Valuation Services portfolio within the Market Intelligence division. This suite combines data, analytics, and valuation models to help clients assess risk and price assets more accurately. The company’s Enterprise Data Organization plays a key role in preparing datasets for AI use, ensuring compatibility with machine learning models. Through this collaboration, both firms aim to deliver AI-ready infrastructure that supports rapid deployment and operational efficiency.

Building Toward Trusted Agentic AI

The alliance also aligns with S&P Global’s broader vision for agentic AI, which it is pursuing through its innovation hub, Kensho. Kensho focuses on developing trusted AI agents that can operate autonomously within enterprise systems. These agents are intended to enhance productivity while maintaining transparency and control. The integration with IBM’s watsonx Orchestrate provides a unified platform for managing these agents across workflows.

IBM’s Agent Catalog, introduced earlier this year, serves as a centralized repository for AI agents and tools. With over 500 pre-built agents available, the catalog simplifies discovery and deployment for enterprise users. The catalog is part of IBM’s effort to make AI orchestration more accessible and modular. As agentic AI continues to evolve, such platforms may become standard components of enterprise architecture.

The term “agentic AI” refers to systems that can act independently to complete tasks, often coordinating with other agents. This approach differs from traditional AI models that require direct human input for each step. According to IBM, agentic frameworks like watsonx Orchestrate are designed to reduce manual effort and improve adaptability in dynamic business environments. The growing interest in agentic AI suggests a shift toward more autonomous, interoperable systems in enterprise technology.