Global tech giant Oracle has announced the latest updates to its “AI Agent Studio” for “Fusion Applications,” thereby transforming it to a complete development platform for building, connecting, and running AI automation and agentic applications. The latest updates also include a new agentic applications builder, along with new capabilities that support workflow orchestration, content intelligence, contextual memory, and ROI measurement.
“As organisations move beyond pilots and begin operationalising AI across the enterprise, they need the ability to tailor AI to their unique workflows, expertise, and operational priorities,” said Chris Leone, executive vice president of Applications Development, Oracle.
“With AI Agent Studio for Fusion Applications, we are helping customers and partners build the foundation for a more autonomous enterprise. Builders can create AI automations and agentic applications using natural language that are powered by enterprise AI agents capable of reasoning, taking action across business systems, and continuously executing processes. This enables organisations to move beyond dashboards and copilots to AI-powered applications that actively run the business, with the governance, trust, and security that enterprises require,” he added.
The latest updates to Oracle AI Agent Studio support the new “Fusion Agentic Applications” and the rapidly growing “Fusion Applications AI ecosystem.” With Oracle AI Agent Studio, organisations will now be able to build, connect, and run AI automation and agentic applications using reusable Oracle, partner, and external agents without traditional application development. In addition, built-in observability, ROI (Return on Investment) measurement, security, auditability, and governance will ensure agents deliver measurable value and operate responsibly at scale.
Businesses will also earn the ability to run reliable, enterprise-grade execution at scale across complex operational processes, thanks to the Oracle AI Agent Studio’s newly-added orchestration capabilities, which will help its users to coordinate multi-step, multi-agent execution with rules that control how work moves between steps, built-in logic, and human oversight.
Explaining further, Chris Leone said, “Content intelligence will help organisations bring together unstructured first- and third-party data with transactional data to expand automation, improve decision-making, and unlock greater value from enterprise information. Through these, businesses will be able to transform unstructured content into usable, contextual signals that agents can understand and act on.”
Not only that, through the AI Agent’s contextual memory, organisations will be getting the opportunity to automate end-to-end processes, reducing repetition and friction by enabling agents to remember context across interactions, workflows, and agent collaboration, apart from learning from user behaviour. Only relevant memories will be retrieved for a specific task, and agents can share context to improve task and outcome coordination.