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Oracle announced an expansion of its AI capabilities, introducing a new generation of role-based AI agents natively integrated into Oracle Fusion Cloud Applications. Rather than launching new standalone products, Oracle’s strategy centres on deep enhancements to its existing Fusion Cloud SCM and CX suites. Derek Gittoes, Vice President of Supply Chain Management Product Strategy at Oracle, clarified that these updates are specialised refinements of the current portfolio.
“They were not brand-new products. So, there are two announcements we had. One is the AI agents. Those are enhancements to existing products that we already have, additional AI agents in procurement, manufacturing, planning, and logistics. And those are designed to support our go-to-market strategy in our target industry.
Our primary target industry is different manufacturing; industrial, automotive, life sciences, and medical devices."
These new AI agents are designed to automate end-to-end workflows, transforming reactive processes into proactive, self-optimising systems. By embedding the agents directly into the Oracle Fusion Cloud Applications suite at no additional cost, Oracle is attempting to bridge the gap between experimental pilots and measurable industrial production.
Oracle’s go-to-market strategy is now laser-focused on vertical industry adoption. And, by tailoring AI agents to the specific nuances of different manufacturing models, it aims to capture high-value sectors that have traditionally struggled with legacy rigidities.
Solving the Process vs. Discrete divide
For industries like automotive, industrial, and medical devices, the focus is on speed and precision. Planning cycle agent automates task coordination to shorten the planning timeline. While the component replacement agent specifically targets Product Lifecycle Management (PLM) to identify and change-order alternative components during supply chain disruptions.
A significant part of the strategy also involves re-engineering of existing systems, order management, inventory, and planning to handle the unique requirements of Process Manufacturing.
“The second announcement was about making enhancements to our existing manufacturing, planning, order management, and inventory systems to handle the nuances of process manufacturing companies, that is to support our go-to-market to drive additional adoption in those particular vertical industries,” Gittoes explained.
13 agents for the supply chain
Key Agents | Functions |
Planning Cycle Agent | Retrieves, assigns, and updates planning tasks within the planning workspace |
Component Replacement Agent | Identifies the component being replaced, recommends alternatives, analyses supply chain impacts, and generates change orders |
Planning Measure Expression Agent | Translates business questions into defined planning calculations, identifies errors, explains issues, and recommends corrections |
Autonomous Sourcing Agent | Identifies requisitions eligible for autonomous negotiation, prepares sourcing events, invites suppliers, and sends notifications in accordance with company policies |
Maintenance Work Order Cost Estimation Advisor Agent | Estimates work order costs based on planned materials, labour, and resource usage and presents consolidated data through a conversational interface |
Outside Processing Shipping Agent | Creates and combines shipping data for components and assemblies sent to suppliers, and helps enable compliance |
Inventory Tasking Agent | Identifies open work, evaluates operator skill sets, availability, and zones, factors in real-time priorities, and assigns tasks automatically. |
Inventory Ageing Advisor Agent | Identifies ageing stock across items and locations, assesses holding costs and impact, recommends actions such as returns and transfers, and executes selected actions. |
Wave Research Advisor Agent | Analyses and summarises batches of warehouse work, identifies issues and root causes, and provides actionable recommendations. |
Task Management Assistant | Detects missing planned ship dates, surfaces key order details for supervisor review, and reprioritises tasks to address potential delays. |
Purchase Order to Sales Order Converter Agent | Extracts data from PDF purchase orders, automatically creates and submits sales orders, summarises exceptions, and learns from user feedback to improve accuracy. |
Product Configuration Agent | Interprets requirements in natural language, recommends and clarifies configuration options, presents side-by-side comparisons, and generates finalised configurations for quotes and sales orders. |
Service Parts Advisor Agent | Uses knowledge base insights and service history to identify the right part to resolve a customer issue and automatically place orders. |
Natively integrated, value-driven innovation
One of the key differentiators that is positioning Oracle strategically in this market is its delivery model. These AI agents run on Oracle Cloud Infrastructure (OCI) and are provided at no additional cost to existing Fusion Application customers. This built-in approach eliminates the friction of secondary integrations and high adoption costs, allowing enterprises to operationalise AI immediately.
The announcement also extended into customer experience (CX) with role-based agents for sales and services. Enhancements like service parts advisor agents that use history to predict and order parts for customer issues before they escalate. And, the Start-of-Day agent that focuses on field technicians, ensuring “first-time fix” rates by summarising daily critical tasks were added in the portfolio.