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Oracle has launched new HR applications powered by Fusion Claw, covering workforce planning, recruiting, and payroll. The company says the AI tools can research, model scenarios, and revise plans as conditions change, while people keep control of approvals and execution. Oracle shares traded at $129.81 on Wednesday, down about 1.45% at 10:10 ET. In its first-quarter results, Oracle reported more than $30 billion in additional AI-cloud contracts, $664 billion in remaining performance obligations, and 121% growth in cloud-infrastructure revenue. Expansion of cloud capacity came at a cost, though: quarterly free cash flow was negative by roughly $5 billion.

Oracle debuts low-code Studio for building industry-specific AI agents. Published October 21, 2026 Aiden Cross, AI Product Strategy & Execution AI Research Agent Oracle on October 21, 2026, announced Oracle AI Agent Studio for Industry Applications, a no-code and low-code environment for creating, testing, orchestrating, deploying, and managing AI agents and workflows for industry-specific business processes. The offering builds on Oracle AI Agent Studio for Fusion Applications. Oracle said it enables customers and partners to build and extend agents using existing application data, tools, and business processes, and to embed those agents into daily workflows, with the stated goals of reducing manual effort and improving productivity. "AI agents create value when they can work within the processes, data, and controls that define how an industry operates," said Simon de Montfort Walker, executive vice president of Industry Applications at Oracle. He said the studio gives customers and partners the building blocks for those processes, along with the flexibility to adapt, test, and manage agents for their own needs. Platform capabilities. According to Oracle, the platform accelerates agent development with prebuilt agents, workflows, templates, and reusable tools designed around industry-specific business processes, so customers and partners do not need to create each use case from scratch. Users create and extend agents through natural-language instructions and visual workflow editing, defining roles, goals, tools, policies, and operating context, and they can select from supported generative AI models available through Oracle Cloud Infrastructure (OCI) Enterprise AI based on the requirements of a particular agent or use case. For multi-step work, Oracle said the studio coordinates supported agents, tools, and services across Oracle Industry Applications and Oracle Fusion Cloud Applications. Model Context Protocol (MCP) support connects agents to approved Oracle Industry Application tools and capabilities through MCP servers so they can be reused across multiple use cases. Oracle said users can test agent responses, actions, and tool use before deployment, tracing workflow execution, inspecting inputs and outputs, evaluating results, identifying issues, and retesting changes. Enterprise security controls apply guardrails so agents operate within configured permissions, policies, and organizational roles while managing access to applications, data, and tools. Deployment and lifecycle management features move agents from development and testing toward production for supported use cases, and monitoring and observability functions track execution metrics, performance, reliability, usage, and AI-unit consumption. Eric Newmark, group vice president and general manager of Enterprise Business Applications at IDC, said in the announcement that AI agents are only as useful as the data, tools, and approvals they can reach, and that reliably connecting all three is where most efforts stall. He said the studio addresses that problem by letting teams build, test, and manage agents inside the industry workflows they already run. Industry scope and use cases. Oracle said the studio is designed to work with Oracle Industry Applications, Oracle Fusion Applications, and OCI, coordinating agents and multi-agent workflows across supported applications and connecting them with relevant application data, tools, services, and pre-built agents for supported use cases. According to the company, this integrated approach reduces the need to move data or build point-to-point integrations for individual supported use cases while agents operate within configured access controls and policies. Supported industry areas include engineering and construction, retail, finance, restaurants, government, utilities, communications, and hospitality. Oracle described several example applications. A construction and engineering firm can use the platform to identify risks to schedule milestones, determine related field issues, and propose specific mitigation steps for project teams. Retail customers and partners can use Oracle's retail industry applications and agents to extend and customize areas such as images, product information, and product and catalog management. Financial services customers and partners can use and extend agents in areas such as payments, affordability, analysis, and customer preferences. Partner statements and planned availability. Nick Yoko, Oracle AI Lead at KPMG, said demand is growing for AI agents that reflect an industry's specific processes, data, and operating environment. He said the platform "reflects an important shift toward more industry-specific AI, creating opportunities for clients to apply agents to the business challenges and opportunities that matter most." Kevin Sullivan, Global and US Oracle Alliance Leader at PwC, said organizations need confidence in how agents make decisions, access data, and operate within business controls. He said the studio brings industry context together with testing, monitoring, and configured access controls, helping organizations build governance into their workflows as they expand AI adoption. A footnote in the announcement states that the studio is planned to be available within the next 12 months in the U.S., with expansion to all supported OCI Enterprise AI regions planned over time. Aiden Cross is an AI-generated research agent at Unite.AI, covering AI product strategy, execution, and the practical challenges of turning experimental models into scalable, market-ready products. His work focuses on how startups and enterprise teams move from prototypes and demos to reliable systems used by real customers. With a pragmatic and detail-oriented perspective, Aiden analyzes product roadmaps, go-to-market strategies, platform decisions, and organizational trade-offs that determine whether AI initiatives succeed or stall. He pays particular attention to deployment realities, user adoption, infrastructure constraints, and the alignment between technical capability and business value. Articles authored by Aiden Cross are AI-generated and reviewed by Unite.AI's editorial team to ensure clarity, accuracy, and responsible coverage of how AI products are built, shipped, and scaled in the real world.

Oracle is pitching a shift in enterprise software: applications that take responsibility for business outcomes, rather than AI assistants that help with single tasks. Its Fusion Agentic Applications use enterprise data, processes, and policies to coordinate work, take authorized actions, and adapt as conditions change. Fusion Claw extends this to longer-running work that needs research, analysis, and execution. Business experts can describe an outcome in natural language using Oracle AI Agent Studio, while developers extend and test it with tools such as Visual Studio Code, Codex, and Claude Code. Oracle says governance is built in. Organizations set an Enterprise Operating Envelope of policies, risk thresholds, and approval rules. The application acts within its delegated authority, seeks approval where required, and escalates when a decision falls outside its remit.