AI Is Moving Closer to the Work

For years, enterprise AI largely lived on the sidelines answering questions, surfacing information, or acting as a standalone assistant. What is changing now is where AI shows up and how it participates in work.

What caught my attention about Oracle AI Agent Studio is that it moves beyond the traditional chatbot model. Instead of sitting outside business processes, AI becomes part of the workflow itself, understanding context, analyzing transactions, and helping users make decisions within the applications they already use.

That shift matters. In my view, the future of enterprise AI is not about creating more conversations with AI. It is about embedding intelligence directly into business processes where decisions are made.

Artificial Intelligence within enterprise applications is evolving rapidly, and Oracle Fusion Applications are moving toward a more intelligent and contextual experience through Oracle Fusion AI Agent Studio. Unlike traditional chatbot-based assistants, Oracle Fusion AI Agents are designed to work within enterprise workflows by understanding business context, analyzing transactions, and assisting users directly inside operational processes.

As organizations explore these capabilities, Oracle Visual Builder Studio (VBS) and custom web applications are becoming important platforms for embedding AI-driven experiences into day-to-day business operations. With capabilities such as Redwood-based extensions, contextual AI interactions, and invokeAsync API integrations, organizations can bring intelligent assistance directly into enterprise workflows instead of relying on standalone AI interfaces.

The Shift from AI Assistants to AI Teammates

Oracle’s recent investments in AI Agent Studio highlight a broader shift toward agentic AI within enterprise applications. Instead of limiting AI to conversational responses, organizations are increasingly looking for AI that can support decisions, guide actions, and participate in operational processes.

Oracle’s AI ecosystem continues to expand across Fusion Applications and industry solutions. Fusion Applications now include hundreds of embedded AI agents across enterprise operations, while Oracle is introducing agentic applications where multiple AI agents collaborate to support complex processes such as financial close operations, hiring workflows, and operational planning.

This broader expansion reflects Oracle’s vision of embedding contextual, workflow-driven AI across enterprise applications rather than limiting AI to isolated assistant experiences.

Embedding AI Through Oracle VBS and Redwood

Oracle Visual Builder Studio is the primary tool for extending Fusion Applications with custom pages, approval flows, and dashboards built on the Redwood Design System. When combined with AI Agent Studio, VBS becomes a powerful environment for embedding contextual AI directly into business experiences, without the need to manage separate AI infrastructure.

This creates opportunities to embed AI-driven capabilities directly into enterprise pages through:

• Intelligent side panels that surface AI-generated summaries or risk indicators alongside an open transaction
• Recommendation cards embedded within approval workflows, for example, a supplier risk score appearing directly inside a purchase order page.
• Guided workflow assistance that helps users navigate complex, multi-step processes through contextual prompts.
• Scoped conversational panels that understand the current record and respond as a transaction-aware advisor rather than a generic chatbot.

Because everything is built on Redwood, AI-powered features look and feel native to Fusion. In my experience, users are far more likely to trust and act on AI recommendations when they appear as a natural part of the application rather than as an external overlay.

Taking AI Beyond the Boundaries of Fusion

What makes these agents particularly powerful is their ability to extend beyond Fusion itself. The invokeAsync API allows organizations to bring AI-driven insights into custom web portals, vendor-facing sites, intranet platforms, and mobile approval apps while maintaining enterprise security and governance controls.

The integration model is straightforward. Applications send the agent identifier along with relevant business context, such as the current transaction or user information, and receive a structured response containing recommendations, summaries, or business insights.

Authentication is managed through Oracle Identity Cloud Service (IDCS) using OAuth 2.0, ensuring that agents operate within the same security boundaries as the user initiating the request. Every call is logged through Oracle Audit, providing traceability and compliance support.

Using this approach, organizations can securely extend Oracle Fusion AI capabilities beyond standard Fusion screens while maintaining enterprise controls.

Where Contextual AI Creates Real Business Value

One aspect I find particularly compelling is how Oracle Fusion AI Agents can be embedded directly into operational workflows while preserving human oversight and decision-making.

Some high-value examples include:

• Procurement: Supplier risk recommendations surface directly within purchase order approval pages, providing delivery performance insights, financial indicators, and dispute history without requiring users to switch screens.
• Accounts payable: Invoice anomaly detection identifies duplicate charges, unusual pricing patterns, and questionable line items while providing clear explanations within the existing workflow.
• HR operations: Employees receive responses to questions about leave policies, benefits, or performance timelines based on their specific profile rather than generic documentation.
• Supply chain: Demand signal summaries consolidate forecast changes, inventory positions, and lead-time variations into actionable recommendations for planners.
• Vendor portals: External supplier portals can use invokeAsync APIs to answer payment status or contract-related questions using live Fusion data, reducing inbound support requests.

Instead of functioning as standalone chatbot interfaces, Oracle Fusion AI Agents are increasingly becoming reusable enterprise AI services that support intelligent, workflow-centric user experiences across applications.

Where Organizations Should Start

As organizations begin adopting AI agents, the focus should not simply be on enabling AI capabilities. The real opportunity lies in embedding them meaningfully within business processes.

A few practical recommendations include:

• Start with contextual, high-friction use cases: Identify processes where users routinely switch between multiple systems, documents, or screens before making a decision. These often represent the highest-value opportunities for contextual AI.
• Use VBS and Redwood extensions for in-app AI surfaces: Avoid the temptation to create standalone AI portals. Instead, embed AI recommendations directly into existing Fusion experiences using VBS page extensions. Adoption tends to happen faster when AI appears within familiar workflows.
• Extend to custom applications via invokeAsync: Map the applications employees, suppliers, and partners use alongside Fusion, whether vendor portals, intranet tools, or mobile approval apps. Identify where Fusion AI Agent capabilities can improve decision-making. The invokeAsync API makes these extensions relatively straightforward.
• Design for humans-in-the-loop: Structure AI-powered pages so that agent recommendations are clearly labelled. Include rationale the user can inspect and require an explicit human action before any AI insight affects a transaction.
• Align integrations with Oracle Fusion security standards: Ensure every invokeAsync integration is registered through IDCS, scoped to minimum necessary permissions, and logged through Oracle Audit. Document data flows for each agent invocation as part of your AI governance inventory.
• Invest in agent quality measurement: Define success metrics before deployment. These might include time saved per decision, recommendation acceptance rate, anomaly false-positive rate, or user satisfaction scores.

Organizations that adopt AI within contextual business processes rather than standalone interfaces will be better positioned to deliver meaningful user experiences and operational value.

The Future of Enterprise AI Is Contextual

What stands out to me is that this is not simply another step in AI adoption. It represents a broader shift in how enterprise applications are designed. The most successful AI experiences will not be the ones that pull users away from their work into separate interfaces. They will be the ones that bring intelligence directly into the flow of work, where business decisions already happen.

The combination of AI Agent Studio, Oracle Visual Builder Studio, and the invokeAsync API creates a complete development stack for contextual enterprise AI: agent logic in Agent Studio, UI experience in VBS with Redwood, and secure portability to any connected application via invokeAsync. The architecture is coherent, the security model is enterprise-grade, and the human-in-the-loop design principle ensures governance without sacrificing intelligence.

As Oracle Fusion AI Agents continue to evolve, the opportunity is not simply to automate more tasks. It is to create more contextual, intuitive, and productive business experiences by bringing human judgment and intelligent systems together inside the processes that matter most.

That is where I believe the real value of enterprise AI will emerge, not as a separate assistant, but as an integral part of how work gets done.

References:

i.    Oracle Fusion Cloud Common Technologies and User Experience 26A What's New, Oracle:  https://docs.oracle.com/en/cloud/saas/readiness/common/26a/common26a/26A-common-wn-f42605.htm#Steps-to-enable-and-configure

ii.    Invoking Fusion AI Agents from External Apps (InvokeAsync), Aravind Ragul, Oracle, March 13, 2026: https://blogs.oracle.com/fusioncoe/invoking-fusion-ai-agents-from-external-apps-invokeasync