According to www.oracle.com, Oracle has introduced 12 new Fusion Agentic Applications for finance and supply chain operations—integrated directly into Oracle Fusion Cloud Applications and powered by coordinated teams of specialized AI agents.
What Are Fusion Agentic Applications?
These applications represent a new class of enterprise software designed to move beyond AI assistance to autonomous execution. They are outcome-driven, proactive, reasoning-based, and engineered for enterprise-scale deployment. Running on Oracle Cloud Infrastructure and powered by industry-leading large language models (LLMs), they operate securely within Oracle Fusion’s existing security framework—accessing unified enterprise data, workflows, policies, approval hierarchies, permissions, and transactional context.
“Finance and supply chain teams are under constant pressure to close faster, respond to disruptions sooner, and deliver more with the same resources, but this is extremely difficult when so much time is still tied up in manual follow-ups, handoffs, and moving work across systems.” — Steve Miranda, executive vice president of Applications Development, Oracle
The 12 New Agentic Workspaces
Each workspace targets a high-friction operational process, transforming manual, fragmented workflows into intelligent, guided, and self-progressing actions. According to the report, the available applications include:
- Claims Settlement Workspace: Improves cash accuracy and accelerates claim settlement while enhancing working capital control.
- Collectors Workspace: Lowers days sales outstanding and increases promise-to-pay conversion rates via continuous, intelligent cash flow management.
- Cost Accounting Close Workspace: Accelerates period close across manufacturing and inventory by surfacing material exceptions and next-best actions.
- Design-to-Source Workspace: Coordinates engineering, supplier, and sourcing decisions to reduce cost, cycle time, and compliance risk.
- Logistics Execution Command Center: Unifies transportation and warehouse data to prioritize exception resolution and minimize fulfillment disruption.
- Maintenance Operations Workspace: Shifts from reactive work-order sorting to proactive, priority-based triage and action.
- Process Manufacturing Workspace: Integrates production, quality, and cost analysis into a single insight-driven workflow to improve batch conformance and reduce variability.
- Product Readiness Workspace: Replaces cross-team manual tracking with a guided workflow to assess supply chain impact and boost launch compliance.
- Production Shift Operations Workspace: Standardizes shift handoffs using readiness checks and carryover flagging to improve output reliability.
- Sales Order Command Center: Centralizes AI-guided resolution of holds, cancellations, returns, and ad hoc customer queries.
- Sourcing Command Center: Streamlines procurement negotiations and high-priority exception handling across disparate tools and inboxes.
- Warehouse Operations Workspace: Proactively surfaces issues across stock, inbound, outbound, and workforce operations—and recommends resolutions.
Enabling Infrastructure and Governance
The agentic applications are supported by Oracle AI Agent Studio, which includes a new Agentic Applications Builder. This tool allows organizations to build, connect, and run AI automation using reusable Oracle, partner, and external agents—without traditional application development. Built-in observability, ROI measurement, and safety controls ensure responsible, measurable, and scalable deployment.
Oracle Fusion Cloud Supply Chain & Manufacturing (SCM) is described in the source as a unified AI-powered platform that integrates supply chain and operations processes to enhance resilience and enable rapid adaptation to market changes. The broader Oracle Fusion Cloud Applications suite—including ERP, HCM, SCM, and CX—is positioned as an integrated set of AI-powered cloud applications aimed at accelerating execution, improving decision-making, and lowering costs.
Source: www.oracle.com
Compiled from international media by the SCI.AI editorial team.
