Enterprise AI adoption is moving from experimentation to execution. Business teams no longer want AI only to answer questions. They want AI agents that can work inside enterprise applications, follow business rules, respect user security, use approved tools, support auditable workflows and help users complete work faster.

Oracle Fusion AI Agent Studio is designed for that shift. It gives organizations a way to design workflows and agents, deploy and extend prebuilt templates, create custom agents and build multi-agent teams inside the Oracle Fusion ecosystem. Oracle positions the platform with the message “Built in. Not Bolted on,” reinforcing that AI agents are becoming part of the application experience rather than a separate technology layer.

For CIOs, business transformation leaders and Oracle application owners, the real question is no longer whether AI agents are coming. The real question is how to deploy them safely, govern them properly and scale them across business processes.

Safe Harbor Note

Oracle’s material includes a safe harbor statement. The roadmap content is intended for information purposes only and is not a commitment to deliver any specific functionality, code or release timing. Oracle also notes that development, release, timing and pricing may change at its discretion.

This is important for implementation planning. Organizations should treat roadmap capabilities as directional and validate availability, licensing and release readiness in their own Oracle environment before making production decisions.

How to Access Oracle AI Agent Studio

Oracle states that AI Agent Studio is generally available in 25C and available in all pods. If users see an error while accessing AI Agent Studio, Oracle recommends creating a Service Request and asking for the AI Agent Studio runtime to be installed in the pods. If no agents are visible inside AI Agent Studio, the likely issue is missing security access or roles. Oracle recommends assigning the appropriate roles and checking configuration in the Security tab.

Another common visibility issue is agent team status. Only published agent teams are shown by default in the Published tab. Users need to use the Draft button to view agent teams that have not yet been published. For implementation teams, this means access readiness should be part of the project checklist. Before business users begin testing AI agents, IT teams should validate pod readiness, runtime availability, security roles, permission groups and published versus draft visibility.

Agents Tab vs Agent Teams Tab

Oracle highlights that there are two ways to create a worker agent:

Agents tab
Agent Teams tab

Agents created from the Agents tab are reusable and cannot be edited directly from the Agent Teams tab. Oracle also notes that the Agent Team should be closed before editing the agent. Agents created from the Agent Teams tab are not reusable, and users cannot search for those agents from the Agents tab.

This distinction matters for long-term governance. If an enterprise expects an agent to be reused across multiple agent teams, it should be created from the Agents tab. If the agent is specific to one team or use case, creating it from the Agent Teams tab may be acceptable.

Single Agent, Multi-Agent Team or Workflow Agent?

Oracle provides a useful decision framework for agent architecture. A single agent is suitable when one role or persona can handle the task entirely. A multi-agent team should be used when the path to an answer is not always clear, when agents need to reason across multiple domains, when teams want faster experimentation and natural conversations, or when the task is exploratory or analytical rather than transactional.

A workflow agent should be used when accuracy and consistency are required, when every action must be logged and auditable, when the process touches systems of record and when the process should be predictable and repeatable. This is one of the most important implementation decisions. Not every AI use case needs a multi-agent design. Not every workflow should be conversational. The right architecture depends on risk, repeatability, auditability and business value.

Topics and Prompts: Why Both Matter

Oracle distinguishes between Topics and Prompts. Topics are reusable instructions to the LLM that can be used across several agents and agent teams. Prompts are specific to an agent and define its behavior. Oracle also explains that topic instructions and prompts are assembled together; they are additive rather than one overriding the other.

To use topics effectively, Oracle states that the agent prompt must refer to topics using the variable {instructions}, which is replaced by the topic prompts at runtime. If topics are added but ignored, the likely reason is that the prompt does not reference the topics list using {instructions}.

For enterprise teams, this is a governance advantage. Common rules such as data privacy, tone, escalation policy, restricted advice, approval requirements and compliance boundaries can be managed as reusable topic instructions instead of being rewritten in every agent prompt.

Deployment Options for AI Agents

Oracle lists four deployment options for AI agents:

Explore tab under Me → AI Agent Studio
Guided Journeys
Within transactions or through Smart Actions in CX
Externally through REST API starting 25D

A key clarification is that Redwood is not required for all AI agent deployment. Oracle states that Redwood is only required to embed agents on transaction pages using Guided Journeys. AI agents can still be accessed without Redwood from the Explore UI under Me or invoked using REST API.

This helps organizations plan deployment based on user experience needs. If the goal is simple exploration, the Explore UI may be enough. If the goal is contextual guidance inside transaction pages, Redwood and Guided Journeys become more relevant.

Deployment and Migration Between Environments

Oracle states that deployment steps are generally the same in production and test environments. However, if Visual Builder Studio is used to deploy agents on transaction pages, those changes need to be migrated using VB Studio.

For migration or export/import between environments, Oracle says Functional Setup Manager can be used to export and import configuration packages. Export/import is supported in 25D. Migrating single agent teams through AI Agent Studio is planned for release 26A.

If migration fails or errors out, Oracle recommends reviewing agent versions and resolving any drafts blocking migration. If technical errors persist, a Service Request should be raised. For implementation teams, this means AI agents should be treated like governed application configuration. They need environment planning, migration discipline, version checks and release control.

Troubleshooting “Agent Not Available” Errors

One common error is: “Sorry, the agent is currently not available right now.”

Oracle recommends checking several areas:

Verify security configuration
Ensure prompts, inputs and configurations are valid
Check that referenced documents in the Document Tool are in Published status
Confirm all Business Object Tools are configured correctly
Check the External REST Tool configuration
Ensure External REST uses HTTPS, not HTTP
Verify that the resource path is the actual endpoint without the instance URL
Note that API Key is not supported in 25C
If issues persist, collect the Trace ID and timestamp from the browser network tab and create an SR

This troubleshooting flow is useful because AI agent errors may not come from the LLM alone. They can come from documents, tools, REST configuration, business objects, security or invalid prompts.

Getting Detailed Error Messages

Oracle states that users can include details on possible errors and agent responses inside the agent prompt. Oracle also notes that more robust error handling is on the roadmap to avoid catch-all messages such as “Sorry, the assistant is unavailable right now.”

This is a practical design point. Enterprises should not rely only on generic fallback behavior. Prompts should define how the agent responds to tool failures, missing data, invalid inputs, authorization problems and retry scenarios.

Getting Answers in Table Format

Oracle recommends using a custom summarization prompt to generate tabulated or table-formatted outputs. The guidance includes giving explicit formatting instructions, such as using HTML tags like <table>, <tr> and <td>, along with styling for readability.

This matters for business users because many enterprise outputs are not simple paragraphs. Users often need comparison tables, approval summaries, supplier lists, exception reports, transaction summaries or structured action plans.

Document Tool: Supported File Types and Upload Discipline

Oracle states that the Document Tool supports Text, PDF and Markdown formats in 25C. There is no strict limit on the number of documents, but uploading too many documents may cause inconsistent responses.

This is an important governance point. More documents do not automatically mean better answers. Enterprises should curate documents, publish only approved content, manage versioning and avoid overloading the agent with unnecessary or conflicting material.

External Apps, Teams, Slack and Transaction Pages

Oracle states that agents can be deployed through Guided Journeys or transaction pages, with Redwood required for embedding. Integration with Microsoft Teams is coming in 26A, while Slack is planned for a future release.

This is important for employee experience design. Some agents may be best used directly inside Fusion pages. Others may be more useful inside collaboration tools where employees already ask questions, review tasks or respond to operational issues.

REST, OIC and SOAP API Support

Oracle confirms that OIC integrations can be invoked using the External REST Tool, provided they are configured properly. Oracle also states that AI Agent Studio does not support SOAP API calls directly. Only REST is supported. For SOAP, Oracle recommends wrapping it with REST.

This is a critical architecture point for enterprises with legacy integrations. AI agents should be integrated through supported REST patterns, and SOAP-based services may need a REST wrapper before they can be used by agents.

File Uploads, Multimodal Support and Chat History

Oracle states that multimodal support is expected in the 26A release. For chat history, Oracle states that history is only available in the session. The Monitoring tab in 25D provides logs for sessions. Future enhancements for persistent chat are part of the roadmap. For enterprise use, this means teams should understand what is retained, where session logs are available and what audit requirements must be met before using agents in sensitive processes.

Multilingual Response Support

Oracle states that agents can support multiple languages, such as Spanish. For global organizations, multilingual support should still be tested by use case. Business terminology, compliance language, HR policy wording and finance instructions may need separate validation before broad rollout.

Custom Agents vs Delivered or Seeded Agents

Oracle clarifies that modifying an agent’s intent, changing system prompts or adding and removing tools can generally make an agent “custom.” Removing a tool may not make it custom, but adding tools or changing intent does. Oracle also notes that the UI will indicate what qualifies as custom starting 25D.

Oracle states that custom agents are chargeable when deployed to production. Delivered or seeded agents can be used within license entitlements. New agents created from scratch are always custom and require an additional SKU. Pricing models and SKU details should be obtained from Sales and external documentation.

For business leaders, this makes agent governance directly connected to cost governance. Teams should decide when to use delivered agents, when to clone, when to customize and when a new custom agent is justified.

Can Templates Be Cloned or Modified?

Oracle states that templates can be cloned or modified, but copying may not allow full modification. As an interim solution, Oracle suggests copying the agent from the Agent tab and copying the Document Tool from the Tools tab. This is useful for implementation teams that need to extend a delivered pattern but preserve enough control over tools, documents and agent behavior.

Improving AI Agent Response Times

Oracle recommends optimizing API response sizes and keeping prompts concise. It also warns that overly complex agents or too many documents in document tools may slow performance. This is a practical reminder that AI performance is not only a model issue. Latency can come from prompt size, tool design, document volume, API payloads and workflow complexity.

Resources, Documentation and Training

Oracle lists several resources for documentation and training, including AI Resource pages in Cloud Customer Connect, What’s New for 25D filtered by AI column, Oracle AI for Fusion Applications Get Started, How do I use AI Agent Studio, AI Agent Collaboration Center, Customer Connect sessions and Oracle University training such as AI Agent Studio Foundations Associate and Oracle AI Agent Studio for Fusion Applications Developers training and certification.

Oracle also notes that recorded sessions, PDF decks and documentation are available on Oracle Customer Connect within 48 business hours after webinars, with free and paid training available on Oracle University.

Oracle AI Agent Studio Platform Capabilities

The platform overview in the deck presents Oracle AI Agent Studio as a platform to build, test and deploy AI agents. It includes capabilities across integration and extensibility, observability and evaluation, LLMs, AI agents, multimodal RAG, workflow nodes, agent marketplace, prompt management and workflow agents.

Key capability areas include:

MCP support
A2A agent cards
Credential store
Microsoft Teams
Slack
Dynamic custom headers
Monitoring and evaluation
Test dataset management
Agent tracing
A/B comparisons
Performance metrics
Token usage
RAG metrics
Enhanced guardrails
Auditing
OpenAI, Meta, Cohere, Google, xAI and Anthropic LLM options
New agent templates
Custom agents
Agent builder assistant
Fusion business object actions
Environment promotion
Multimodal RAG
SharePoint integration for RAG on external documents
Workflow nodes such as agent node, document processor, LLM, vector read/write, for-loop iteration, parallel execution, switch branching, human-in-the-loop, code/tool nodes and triggers

This breadth shows that AI Agent Studio is not simply a chatbot interface. It is an agent lifecycle and orchestration platform for enterprise applications.

Prebuilt Templates in 25C and 25D

Oracle lists a large set of prebuilt templates across 25C and 25D. The 25C templates cover public sector, service, sales and marketing, human resources, supply chain, finance and procurement. Examples include Service Request Triage Agent, Account Advisor Agent, Sales Analyzer, Benefit Analyst, Pay Analyst, Procurement Policy Advisor, Quality Inspection Advisor, Material Handling Agent and Claims Policy Advisor.

The 25D templates expand into CPQ, service, incentives, HCM, supply chain and manufacturing, procurement, ERP and industry, and public sector. Examples include Quote Advisor, Case Analyzer Agent, Contract Summarization Agent, Lead Advisor Agent Team, Deal Advisor Agent Team, Payroll Run Analyst, B2B Message Converter, Product 360 Advisor, Supplier Portal Advisor, Purchase Requisition Status Advisor and Access Request Assistant. These templates give enterprises a practical starting point and reduce the need to build every agent from scratch.

Practical Prompt Patterns: Session, Unique ID and Pagination

Oracle includes three practical prompt examples that are especially useful for enterprise agent builders.

Get User Session

The agent retrieves user identification details once at the beginning of a conversation using the get User Session tool, then reuses the employee’s Person Number and Server Time throughout the conversation.

Get Unique ID

The example uses a business object called COE_INVENTORY_BALANCE and calls an inventory on-hand balance function using item number. The agent extracts the unique ID from the self-link or fallback key and encodes it for API usage.

Pagination

The pagination example uses a COE Suppliers business object with an offset parameter. The agent determines whether the user wants to view more suppliers, calls the API with the current offset, displays results and asks if the user wants the next five suppliers. If the user says no, the agent stops pagination and does not call the REST tool again.

These examples show that enterprise agent prompts need operational discipline. They must manage state, avoid unnecessary API calls, handle identifiers correctly and respond based on user intent.

Choice of LLMs

Oracle’s LLM slide shows model options across OpenAI, Meta, Anthropic, Google, xAI and Cohere. The slide includes GPT-5, GPT-4.1, GPT-4o, Gemini 2.5 Flash, Gemini 2.5 Pro, Claude Sonnet 4, Claude Haiku 3.5, Grok 3, Llama models and Command R. It also indicates both comes with Fusion and bring your own options.

For enterprise AI strategy, model choice matters. Different use cases may require different balances of reasoning, speed, cost, multimodal ability and governance.

What Enterprises Should Prioritize Before Production

Before deploying Oracle AI agents into production, organizations should create a structured readiness plan.

Key priorities include:

Confirm AI Agent Studio access and runtime readiness
Validate roles, permission groups and security configuration
Decide whether each use case needs a single agent, multi-agent or workflow agent
Use topics for reusable governance instructions
Keep prompts concise and specific
Publish and validate documents before using the Document Tool
Avoid excessive document uploads
Use REST-based architecture for external APIs
Wrap SOAP services with REST where required
Define migration and environment promotion strategy
Check whether customization affects licensing
Create troubleshooting and SR escalation procedures
Monitor performance, response quality and user adoption
Train administrators and business users

The right implementation discipline will determine whether AI agents remain pilots or become reliable business tools.

How NexInfo Can Help

NexInfo helps organizations adopt Oracle Fusion AI Agent Studio with a practical, enterprise-ready approach.

NexInfo can support:

Oracle AI Agent Studio readiness assessment
Access and security role validation
AI agents use case discovery
Single-agent, multi-agent and workflow-agent design
Delivered template evaluation
Custom agent planning
Topics and prompt design
REST API and OIC integration planning
Document Tool governance
Smart Actions and Guided Journey deployment planning
Migration and environment promotion strategy
Troubleshooting framework
Guardrail and compliance design
Performance optimization
Testing, monitoring and adoption support

NexInfo helps enterprises move from AI experimentation to governed, scalable and business-aligned AI execution.

Conclusion

Oracle Fusion AI Agent Studio gives enterprises a structured path to build, deploy and govern AI agents inside Fusion Applications. The platform supports access control, reusable agents, agent teams, topics, prompts, deployment options, migration, REST integrations, document tools, workflow agents, troubleshooting, custom agent governance, platform monitoring and LLM choice.

The most successful AI agent programs will not simply focus on building agents quickly. They will focus on building them correctly — with security, governance, performance, migration, monitoring and business ownership in place.

NexInfo helps organizations adopt Oracle Fusion AI Agent Studio with the right roadmap, architecture and implementation discipline.

FAQ
How do I access Oracle AI Agent Studio?

Oracle states that AI Agent Studio is generally available in 25C and available in all pods. If an error appears while accessing it, Oracle recommends creating a Service Request and asking for AI Agent Studio runtime to be installed in the pods.

Why can’t I see agents in AI Agent Studio?

The likely reason is missing security access or roles. Oracle recommends assigning appropriate roles and checking configuration in the Security tab.

Why can’t I see all agent teams?

Only published agent teams are displayed by default in the Published tab. Use the Draft button to view agent teams that are not yet published.

Should I create an agent from the Agents tab or Agent Teams tab?

Create reusable agents from the Agents tab. Agents created from the Agent Teams tab are not reusable and cannot be searched from the Agents tab.

What is the difference between Topics and Prompts?

Topics are reusable instructions used across agents and agent teams. Prompts are specific to an agent and define its behavior. They are additive, and the agent prompt should reference topics using the {instructions} variable.

What are Oracle AI agent deployment options?

Oracle lists deployment through the Explore tab, Guided Journeys, within transactions or Smart Actions in CX, and externally through REST API starting 25D.

Is Redwood required to deploy AI agents?

No. Oracle states that Redwood is only required to embed agents on transaction pages using Guided Journeys. AI agents can be accessed without Redwood from the Explore UI or invoked using REST API.

How do I migrate AI agents between environments?

Oracle recommends using Functional Setup Manager to export and import configuration packages. Export/import is supported in 25D, and single agent team migration through AI Agent Studio is planned for 26A.

How do I fix the “agent not available” error?

Oracle recommends checking security configuration, prompts, document publication status, business object configuration, External REST Tool setup, HTTPS usage, resource path accuracy and unsupported API Key usage in 25C. If needed, collect Trace ID and timestamp and create an SR.

What file types are supported in the Document Tool?

Oracle states that Text, PDF and Markdown formats are supported in 25C. There is no strict document count limit, but too many documents may cause inconsistent responses.

Can AI Agent Studio call OIC or external APIs?

Yes. Oracle states that OIC integrations can be invoked using the External REST Tool with proper configuration.

Does AI Agent Studio support SOAP APIs?

No. Oracle states that only REST is supported. SOAP APIs should be wrapped with REST.

Are custom agents chargeable?

Oracle states that custom agents are chargeable when deployed to production. Delivered or seeded agents can be used within license entitlements, while new agents from scratch are always custom and require an additional SKU.

How can agent response time be improved?

Oracle recommends optimizing API response sizes, keeping prompts concise and avoiding overly complex agents or too many documents in document tools.

How can NexInfo help with Oracle AI Agent Studio?

NexInfo helps with AI Agent Studio readiness, security validation, agent architecture, template evaluation, prompt and topic design, workflow agent setup, REST and OIC integration planning, deployment, migration, troubleshooting, governance and user adoption.

Oracle Fusion AI Agent Studio Implementation Guide: From Access to Production-Ready AI Agents