Core Insights - IBM has announced the launch of three new AI agents on the Oracle Fusion Applications AI Agent Marketplace aimed at enhancing operational efficiency for Oracle Fusion Cloud Applications customers [1][4] - The new agents are built using Oracle AI Agent Studio and are designed to automate processes and workflows within Oracle Fusion Applications [1][5] - IBM plans to introduce additional agents for HR and supply chain, expanding its offerings in the Oracle ecosystem [1][2] Summary by Categories New AI Agents - The three new AI agents include: - Intercompany Agent: Automates the review of intercompany agreements [5] - Smart Sales Order Entry Agent: Streamlines the sales-order creation process by generating relevant data for the order-to-cash process [5] - Requisition to Contract Agent: Manages the workflow of converting purchase requisitions to contract purchase orders [5] Technology and Development - The agents are developed on IBM watsonx Orchestrate, an enterprise-grade AI solution that supports the deployment and governance of AI agents [2] - Watsonx Orchestrate operates on Red Hat OpenShift AI, providing a multi-agent approach that integrates with Oracle's AI offerings [2] Strategic Partnership - The collaboration between IBM and Oracle aims to leverage their combined expertise in enterprise AI and business transformation to drive innovation and competitive advantage for clients [1][4] - Oracle plans to make the IBM Granite 4.0 family of AI models available through its Oracle Cloud Infrastructure Data Science [2]

Core Insights - S&P Global and IBM have formed a strategic alliance to integrate IBM's watsonx Orchestrate framework into S&P Global's offerings, starting with supply chain management [1][2] - The collaboration aims to provide AI-powered tools to enhance insight and visibility in supply chain and vendor selection, leveraging S&P Global's proprietary data and analytics [2][3] Group 1: Partnership Objectives - The partnership seeks to empower organizations to improve procurement strategies, manage risks, and make informed decisions, ultimately driving greater efficiency in a complex market [3] - S&P Global plans to expand the integration of IBM AI technology into additional risk intelligence services within its Market Intelligence division [2][3] Group 2: Product Offerings - The new offering will include AI agents that combine data across procurement, trade, country, and supplier risk domains to expedite decision-making in supply chain management [2] - IBM's watsonx Orchestrate includes an Agent Catalog featuring over 500 pre-built agents and tools to streamline workflows across businesses [4] Group 3: Market Positioning - S&P Global's supply chain solutions are part of its Risk & Valuation Services portfolio, which aims to provide differentiated data and analytics to help identify risk exposures and create market transparency [3] - The collaboration aligns with S&P Global's vision for agentic AI, focusing on developing trusted AI agents to enhance enterprise value [3]

Core Insights - The next wave of AI is focused on generating revenue rather than just providing tools, which is seen as a trillion-dollar opportunity by industry leaders [2] - The transition from large models to intelligent agents marks a new era in AI, emphasizing automation and cash flow generation [2] - Companies' core competitiveness will depend on customized AI applications and quantifiable business outcomes [2][3] Data and Integration - High-quality data is essential for companies to realize the benefits of AI, with data integration being a critical factor [3] - The integration of AI with traditional automation technologies is a key focus for future AI development, particularly in manufacturing [3][4] Intelligent Agents - The demand for intelligent agents is growing, with various companies launching advanced AI models and solutions [6][7] - IBM has introduced a comprehensive enterprise-ready AI agent solution, emphasizing collaboration and integration with existing IT assets [7][8] Application and Use Cases - Intelligent agents are being applied in specific business scenarios, such as customer service and R&D, to enhance efficiency and reduce operational costs [10][11] - Companies are encouraged to start with small, specific use cases to validate ROI before scaling up [12] Market Trends - The sales of AI agents and related products are projected to significantly increase, with estimates suggesting revenues could reach $125 billion by 2029 and $174 billion by 2030 [6] - The competitive landscape is shifting as companies seek to leverage AI agents for greater returns on investment [12]