From Recording Work to Agentic AI Applications That Execute It
Oracle’s new AI-native builder for Oracle AI Agent Studio inside Fusion Applications is a development environment that lets enterprises design, run, and govern agentic AI applications directly against their core business workflows instead of relying on disconnected bots or external automation platforms, combining no-code, low-code, and pro-code tools under a shared security and governance layer. This move matters more than yet another AI assistant. Oracle is saying the future of enterprise software is outcome-driven: systems that “actively drive and execute outcomes,” not just systems of record. By tying agents to Fusion business objects, approvals, and audit trails, Oracle is pushing agentic AI out of experimental corners and into the daily heartbeat of finance, supply chain, and CX operations. That’s a bold bet on where real AI value will come from: execution trust, not novelty.
Inside the Oracle Fusion Builder: No-Code Meets Pro-Code Under One Roof
Oracle’s AI-native Fusion builder is less a single tool than a layered builder model. At the top, business users get no-code AI development through natural language in the Agentic Applications Builder, describing outcomes they want rather than writing scripts. At the bottom, developers and partners can work as they always have: using the AI Studio Skill with Visual Studio Code, command-line interfaces, Git workflows, CI/CD, and AI coding assistants such as OpenAI Codex and Claude Code. The critical change is that all these paths produce the same kind of artifact: Fusion Agentic Applications that inherit Fusion’s security, approvals, policies, and audit logging. Oracle is openly widening the builder audience, betting that mixing business-led no-code AI with disciplined engineering practices inside one governed platform will cut through AI backlog and make agents a shared asset, not a skunkworks experiment.
Why Governance Is the Real Differentiator in Enterprise AI
Oracle’s sharp distinction between isolated AI agents and full agentic AI applications is not marketing; it reflects where enterprise AI projects are stuck. Many organizations have rushed into generative AI, but proofs of concept often fail to become production systems. When automations live outside the ERP or CX platform, teams must still solve identity, data access, approvals, audit trails, observability, and lifecycle management before trusting AI to execute real work. Oracle’s stance is blunt: those controls should be part of the runtime from day one. Fusion Agentic Applications run inside Fusion, act on Fusion business objects and workflows, inherit security and governance, and log every action for auditability. That makes enterprise AI governance a feature, not an afterthought. If agentic apps will decide and execute tasks that affect customers, revenue, and compliance, the platform that can prove who did what, when, and under which policy will win the next phase of AI competition.
Practical Impact for Fusion Users: Who Builds What, Starting Now
For Fusion customers, the launch turns Oracle AI Agent Studio from a vendor-only tool into a shared builder space. Oracle already ships more than 1,000 AI agents through Fusion Applications and has introduced 22 Fusion Agentic Applications earlier this year; now customers and partners can extend them or build their own on the same platform Oracle uses. The studio, available at no additional cost, includes orchestration, testing, validation, and built-in security. Business users can describe new agentic workflows in natural language, while developers apply familiar debugging and Git-based lifecycle management—all in one governed environment. A public GitHub repository will add templates, starter projects, and reference architectures, and more than 80,000 certified experts have already been trained in Oracle AI Agent Studio. The real question for Fusion customers is no longer whether agents will be embedded, but how far they want to customize and govern agentic execution inside their own processes.
Competitive Stakes: Execution Trust as the New AI Battleground
Oracle’s builder release is also a strategic shot at the broader enterprise AI market. ERP and CX vendors are racing to offer agentic workflows, AI-assisted development, and marketplaces of reusable agents. But the test is moving away from flashy demos toward governed application layers that sit where customer, financial, operational, and employee data already lives. By positioning Fusion as both the system of record and the system where AI-powered work is executed, Oracle is arguing that agentic applications should be first-class citizens of the suite, not bolt-on automations. Agentic applications will compete on execution trust, not just automation speed. In that contest, Oracle’s AI-native Fusion builder tries to change who can build—from a small developer elite to a cross-functional group spanning business and IT—without relaxing enterprise AI governance. If Fusion customers embrace that shift, Oracle could turn agentic AI from a feature into the backbone of how its applications run.
