Analyst(s): Keith Kirkpatrick
Publication Date: July 20, 2026
Oracle has introduced an AI-native builder experience that enables customers and partners to create Fusion Agentic Applications within existing business workflows, governance controls, and approval structures.
What Is Covered in This Article:
- Oracle’s new builder experience combines no-code, low-code, and pro-code development within Oracle Fusion Applications.
- Fusion Agentic Applications coordinate specialized AI agents to execute work through business objects, workflows, policies, approvals, and logged actions.
- Business users can build with natural language, while developers can work with Visual Studio Code, Codex, Claude Code, CLIs, and Git.
- Oracle aims to reduce the technical and governance barriers that prevent organizations from moving AI applications from prototypes into production.
- The broader market test will be whether enterprises trust agentic applications to execute business processes, not merely recommend actions.
The News: Oracle introduced an AI-native builder experience for Oracle AI Agent Studio for Fusion Applications that enables customers and partners to create and run Fusion Agentic Applications directly within Oracle Fusion Cloud Applications. The experience combines no-code, low-code, and pro-code development, allowing business users to start with natural language while developers use tools including Visual Studio Code, OpenAI Codex, Claude Code, CLIs, and Git-based workflows.
Fusion Agentic Applications use teams of specialized AI agents to coordinate and execute work through Fusion business objects, workflows, policies, approvals, and logged actions. Oracle AI Agent Studio is available at no additional cost and includes orchestration, testing, validation, and built-in security, while a new public GitHub repository will provide templates, starter projects, sample applications, reusable assets, and reference architectures.
Will Oracle’s Fusion-Native Approach Solve Agentic AI Governance?
Analyst Take: Oracle is making a clear argument with Fusion Agentic Applications: enterprise software should execute work, not merely record it or suggest the next step. The applications can coordinate specialized agents, access Fusion business objects, initiate workflows, follow policies, obtain approvals, and log actions inside the same system. This matters because many AI projects work in demonstrations but stall when organizations confront permissions, security, testing, and accountability. Oracle has chosen the right battleground by focusing on controlled execution inside business processes rather than adding another AI interface.
Governance Is Oracle’s Strongest Argument
Oracle is right that enterprises should not bolt governance onto an AI application after building it. An application created outside Fusion still needs identity controls, data access rules, approvals, audit trails, observability, security, and lifecycle management before it can execute business-critical work. Oracle avoids much of that reconstruction by placing Fusion Agentic Applications inside the environment where those controls and workflows already operate. Its testing, debugging, human approval, audit, and replay capabilities also give organizations ways to review decisions and investigate failures. That makes governance the substance of Oracle’s offer, not a supporting feature added to make autonomous execution sound safer.
More Builders Mean More Risk
Oracle is widening access by giving business users natural-language tools while allowing developers to work with Visual Studio Code, CLIs, Git, Codex, Claude Code, debugging, and CI/CD workflows. Business users may understand an operational process better than a centralized development team, but that knowledge does not automatically qualify someone to deploy software that can execute the process. According to Futurum Group’s 1H 2026 Enterprise Software Decision Maker Survey Report, 56.0% of enterprise decision-makers still prefer to build most applications in-house. That preference makes Oracle’s combination of natural-language development, professional coding tools, reusable assets, and native Fusion controls particularly relevant to how enterprises want to create software. Oracle’s builder model will deliver value only if customers define who can build, approve, deploy, monitor, modify, and retire every agentic application.
Fusion Agentic Applications Must Improve Business Processes
Many customer experience failures begin in collections, workforce operations, supply chains, approvals, and service processes rather than in customer-facing interactions. An AI assistant may produce a useful response, but that response achieves little when the underlying process remains delayed or fragmented. Fusion Agentic Applications could address this problem by coordinating the operational steps that determine whether an issue gets resolved, escalated, or left waiting. Oracle specifically identifies improving collections, reducing service escalations, optimizing workforce operations, accelerating financial close, and streamlining supply chain execution as potential outcomes. Customers should judge these applications by faster resolution and fewer operational failures, not by the number of agents available in Oracle’s product catalog.
Oracle Still Has to Prove Execution
Oracle can point to more than 1,000 AI agents across Fusion Applications, 22 Fusion Agentic Applications launched earlier in 2026, and over 80,000 certified AI Agent Studio experts. Those figures demonstrate the size of Oracle’s product and partner effort, but they do not prove that agent teams can execute complex business processes consistently. The real test is whether the applications respect approvals, explain actions, surface exceptions, maintain audit trails, and deliver measurable operational improvements. Expanding Oracle AI Agent Marketplace to include complete agentic applications may accelerate adoption, but reusable applications still require disciplined testing and ownership. Until customers can connect Fusion-native execution to better business outcomes, Oracle has a convincing architecture rather than a proven operating model.
What to Watch:
- Enterprises must determine who can build, approve, deploy, monitor, modify, and retire Fusion Agentic Applications as development expands beyond traditional engineering teams.
- Oracle will need to demonstrate that specialized agent teams can coordinate complex processes consistently while respecting permissions, policies, approvals, and exception-handling requirements.
- Customers should measure whether Fusion Agentic Applications reduce service escalations, accelerate resolution, improve collections, shorten financial close, or remove supply chain delays.
- The expanded Oracle AI Agent Marketplace will test whether reusable agentic applications can support enterprise-specific processes without creating additional governance and lifecycle complexity.
- CIOs and application leaders must decide whether building inside Fusion’s existing controls produces better operational outcomes than running agents through external orchestration layers.
- Wider adoption will depend on whether organizations trust agentic applications to execute actions—not merely recommend them—within business-critical finance, workforce, service, and supply chain processes.
See Oracle’s complete announcement on the new AI-native builder experience for Oracle Fusion Applications.
Declaration of generative AI and AI-assisted technologies in the writing process: This content has been generated with the support of artificial intelligence technologies. Due to the fast pace of content creation and the continuous evolution of data and information, The Futurum Group and its analysts strive to ensure the accuracy and factual integrity of the information presented. However, the opinions and interpretations expressed in this content reflect those of the individual author/analyst. The Futurum Group makes no guarantees regarding the completeness, accuracy, or reliability of any information contained herein. Readers are encouraged to verify facts independently and consult relevant sources for further clarification.
Disclosure: Futurum is a research and advisory firm that engages or has engaged in research, analysis, and advisory services with many technology companies, including those mentioned in this article. The author does not hold any equity positions with any company mentioned in this article.
Analysis and opinions expressed herein are specific to the analyst individually and data and other information that might have been provided for validation, not those of Futurum as a whole.
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Author Information
Keith Kirkpatrick is VP & Research Director, Enterprise Software & Digital Workflows for The Futurum Group. Keith has over 25 years of experience in research, marketing, and consulting-based fields.
He has authored in-depth reports and market forecast studies covering artificial intelligence, biometrics, data analytics, robotics, high performance computing, and quantum computing, with a specific focus on the use of these technologies within large enterprise organizations and SMBs. He has also established strong working relationships with the international technology vendor community and is a frequent speaker at industry conferences and events.
In his career as a financial and technology journalist he has written for national and trade publications, including BusinessWeek, CNBC.com, Investment Dealers’ Digest, The Red Herring, The Communications of the ACM, and Mobile Computing & Communications, among others.
He is a member of the Association of Independent Information Professionals (AIIP).
Keith holds dual Bachelor of Arts degrees in Magazine Journalism and Sociology from Syracuse University.
