Oracle is going all-in on embedded AI.

At its AI World Tour, the company introduced a new suite of role-based AI agents within Oracle Fusion Cloud Applications, aimed squarely at helping enterprises deliver intelligent customer experiences (CX) at scale. The agents, built with Oracle AI Agent Studio for Fusion Applications, are designed to operate inside existing marketing, sales, and service workflows—no swivel-chair integrations required.

The pitch is straightforward: unified data in, automation and predictive insight out.

AI Agents, Embedded — Not Bolted On

Unlike standalone AI copilots that sit on top of business systems, Oracle’s agents are prebuilt and natively integrated into Fusion Applications and run on Oracle Cloud Infrastructure (OCI). Oracle says they’re available at no additional cost to existing Fusion customers.

That’s notable. As enterprise AI adoption accelerates, pricing models are under scrutiny. Bundling AI agents directly into core workflows lowers friction—and potentially speeds up adoption.

According to Chris Leone, EVP of Applications Development at Oracle, the goal is to shift enterprises from reactive processes to proactive, intelligent workflows that increase customer lifetime value.

Marketing: From Campaign Planning to Asset Selection

Oracle’s marketing agents focus on reducing manual coordination and improving campaign precision. Highlights include:

• Program Planning Agent to define campaign goals, audiences, and messaging.

• Program Brief Agent to align product, marketing, and sales teams with automated summaries of objectives and tactics.

• Program Orchestration Agent to convert strategy into executable assets.

• Buying Group Agent to segment accounts and identify high-probability buyers.

• Customer Insights Agent to ground campaigns in real operational signals such as billing status and renewal timing.

• Audience Analysis Agent to optimize investment strategies and segmentation.

• Copywriting Agent to draft brand-aligned emails and web content.

• Image Picker Agent to recommend campaign visuals from approved assets.

Taken together, Oracle is clearly targeting one of marketing’s biggest pain points: fragmented planning and execution across teams and tools.

Sales: From Insights to Quote Generation

On the sales side, Oracle is embedding intelligence into research, pricing, and renewals:

• Contact Insights Agent surfaces relationship data and account influence mapping.

• Quote Generation Agent analyzes inputs—emails, drawings, requirements—and assembles configurations using correct pricing templates.

• Renewal Agent monitors contract health and flags margin risk while generating renewal briefs.

• My Territory Agent highlights expansion opportunities, anomalies, and risk across accounts.

The common thread? Turning CRM data into actionable recommendations without forcing sellers to leave their workflow.

Service: Speed and First-Time Fix Rates

In service operations, automation targets efficiency and response quality:

• Start-of-Day Agent provides technicians with personalized task summaries.

• Work Order Scheduling Agent aligns technician skills, parts readiness, and customer availability.

• Customer Self Service Agent answers questions, creates service requests, and escalates when needed.

• Attachment Processing Agent extracts key details from uploaded files to accelerate case resolution.

For field service and support teams, this could mean fewer delays and higher first-time resolution rates—metrics that directly impact customer satisfaction.

The Bigger Strategy: AI Agent Studio

Beyond prebuilt agents, Oracle is also positioning AI Agent Studio for Fusion Applications as a development layer. Customers and partners can create custom AI agents and agent teams, extending automation across enterprise workflows.

That move reflects a broader shift in enterprise AI: from isolated copilots to orchestrated agent ecosystems embedded inside business systems.

Why It Matters

Every major enterprise software vendor is racing to deliver AI-powered workflows. The differentiation increasingly lies in:

• Depth of native integration

• Access to unified cross-functional data

• Cost transparency

• Ease of customization

By embedding AI agents directly into Fusion CX and bundling them into existing subscriptions, Oracle is aiming to remove common barriers to enterprise AI rollout.

If customers embrace the model, Oracle’s bet on deeply integrated, role-based agents could help solidify Fusion Applications as more than just a cloud ERP and CX suite—it becomes an AI execution layer for the enterprise.

In the AI arms race, integration may matter more than innovation alone.

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