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Oracle’s agentic AI strategy: What it means for enterprise operations
May 18, 2026 · Authored by Kevin Ruis and Meghan Loomis
Artificial intelligence (AI) is no longer a feature bolted onto enterprise software – for Oracle, it is quickly becoming the connective layer for the entire platform. Oracle’s latest AI strategy centers around a bold, data-centric approach: rather than routing data through a patchwork of external tools and models, Oracle is bringing AI directly to where enterprise data already lives, which is Oracle Fusion Cloud Applications.
With the introduction of AI Agent Studio and Fusion Agentic Applications, Oracle is extending this strategy beyond embedded AI features to a platform where AI agents can be configured, orchestrated, and deployed to execute end-to-end business processes.
This shift matters because most organizations have already learned that AI experiments rarely survive contact with real-world business data. Historically, data has been scattered across systems, structured differently and governed by inconsistent access rules. Oracle’s answer is to collapse that complexity, embedding AI processing into the data layer itself to reduce friction, improve reliability and give organizations more control over how information is accessed and used.
1. From assistance to execution
Oracle’s strategy is to shift from AI that assists users to AI that executes business processes. With the introduction of Fusion Agentic Applications, Oracle is enabling AI agents to interact with enterprise data, coordinate workflows and create role-based workspaces for users such as managers, administrators and specialists.
Through AI Agent Studio, these agents can also be configured and extended by organizations to operate across HCM, ERP and SCM workflows, enabling cross-functional orchestration rather than siloed task execution.
These are not standalone tools. They are embedded in Fusion, which remains the system of record. The agents leverage Fusion data and processes to:
This represents a move where work is increasingly orchestrated by AI rather than manually executed across multiple screens, reducing the need to navigate across modules or piece together fragmented processes.
2. Purpose-built agentic applications
Oracle has now released 22 agentic applications, that are accessible and configurable through AI Agent Studio.
Oracle Fusion Agentic Applications represent the next evolution of enterprise software, where AI agents are embedded directly into business processes to execute work autonomously.
Unlike traditional applications that rely on user input to initiate and complete tasks, agentic applications are designed to operate with a defined goal, continuously reasoning, making decisions, and taking action across systems.
These applications:
Combine multiple AI agents working together toward a shared objective
Operate within Oracle Fusion Applications using real-time enterprise data
Adapt dynamically based on context, inputs, and process outcomes
Span functional domains such as HCM, ERP and SCM
Rather than interacting with systems through screens and workflows, users engage with role-based workspaces where agents handle coordination, execution, and decision support.
These applications are designed around real business processes. For example:
A recruiting workspace that allows recruiters to manage requisitions, candidates and offers in one place
Payroll and absence workflows that streamline approvals and transactions
Role-specific workspaces that consolidate fragmented tasks into a single interface
Cross-functional agents that span multiple functional domains (e.g., hire-to-retire, procure-to-pay)
Agents within these applications interact with each other to complete processes, effectively creating AI-driven work environments rather than isolated automations.
In practice, this can significantly reduce handoffs and manual coordination, especially in high-volume, process-heavy areas like human resources (HR) and finance while giving users a more intuitive, consolidated experience. Over time, this creates a composable ecosystem of agents that can be orchestrated into broader enterprise workflows.
3. Security and data governance at the core
A defining element of Oracle’s AI strategy is its approach to data security and isolation. Within Fusion:
Access to agents can be restricted by role (employee, manager, admin, specialist)
Data visibility can be controlled at a granular level
Organizational data remains within the organization’s environment
Importantly, data entered into Oracle’s AI environment is not shared across external models or global Large Language Models (LLMs). As a result, organizations can enable AI usage internally without exposing sensitive data to public tools like ChatGPT or other external platforms. In an environment where employees are already experimenting with AI tools, this provides a more controlled and secure way to incorporate AI into everyday workflows. This architecture enables organizations to operationalize agentic AI within enterprise guardrails, ensuring that autonomous execution remains aligned with security, compliance and governance policies.
4. LLM strategy: Performance and practicality
Oracle’s broader AI strategy is pragmatic and designed around choice and adaptability. The agents powering the workspaces run on the LLMs that an organization selects. Through Oracle Cloud infrastructure (OCI), Oracle supports a wide range of models out of the box, including OpenAI, Anthropic, Meta, Google, Cohere and xAI.
This means that when an agent is executing tasks, it can leverage the most appropriate model for that specific task, all within the organization’s security framework and against its own data. Rather than betting on a single model provider, Oracle’s approach is inherently model-agnostic and future-proof.
Through AI Agent Studio, organizations can also define how and when different models are used across agents, enabling optimization of cost, performance and accuracy at the workflow level.
5. AI Agent Studio: Customization as a necessity
While Oracle delivers prebuilt agents, it recognizes that no two organizations use enterprise systems the same way. AI Agent Studio enables organizations to:
Configure and tailor agents to their processes
Build custom agentic applications
Adapt workflows to match industry and organizational requirements
This is especially important because out-of-the-box agents often do not fully align with how organizations actually operate. In practice, many agents become custom by necessity, requiring adjustment to fit real-world processes. AI Agent Studio effectively becomes the control plane for enterprise AI, enabling organizations to move from consuming AI features to designing and operationalizing AI-driven processes.
5. Measuring ROI
Oracle is introducing return on investment (ROI) dashboards to demonstrate the value of AI through metrics such as time savings, cost reduction and productivity gains.
What’s notable is that Oracle is embedding ROI measurement directly into the platform itself. The ROI dashboard tracks impact at multiple levels, such as agent, workflow and functional, so value realization is directly tied to how the system is used. Rather than treating ROI as a separate, retrospective exercise, measurement becomes part of day-to-day execution. This includes visibility into how individual agents and multi-agent workflows contribute to outcomes, enabling continuous optimization of AI-driven processes.
This is a meaningful shift. Instead of trying to justify AI investments months after deployment, organizations can begin to see how AI is performing in real time as processes are executed.
Making agentic AI work for your organization
Oracle’s AI strategy is about redefining how work is performed within enterprise systems. The shift toward agentic applications creates the potential to automate end-to-end processes rather than individual tasks, embed AI directly into daily workflows instead of treating it as a separate tool and enable faster, more consistent execution across functions such as HR, finance and operations.
Successful adoption of Oracle Cloud and increasingly, agentic AI requires both technical experience and industry context. Standard functionality alone is rarely enough; value is unlocked when solutions are tailored to real-world operating models.
Baker Tilly, a premier Oracle PartnerNetwork member, brings deep capabilities across Oracle’s cloud ecosystem, including ERP, HCM, SCM, and EPM, to help organizations translate technology into tangible outcomes. With experience supporting organizations ranging from mid-market to Fortune 50, Baker Tilly helps clients navigate the complexity of Oracle transformations by aligning AI and cloud capabilities to business strategy. Assess your organization’s preparedness for AI adoption by completing our readiness checklist today!
