Oracle has introduced a new AI Native Builder experience that increases the pool of organizations that can create and run agent applications.
This announcement expands Oracle’s efforts beyond embedded AI assistants and standalone agents to results-driven applications that can coordinate tasks, trigger workflows, follow approvals, and take actions within existing enterprise systems.
CX leaders must now consider whether AI can reliably support and execute business processes within their existing operating environment.
Chris Leone, executive vice president of Oracle application development, said: explained The new builder experience reflects a broader shift to enterprise applications that can proactively adjust and execute results.
“Enterprise software is moving from a system that records work to a system that proactively drives and executes results,” he said.
“This new builder experience enables customers and partners to build Fusion Agentic Applications that run natively within Oracle Fusion Applications, where business objects, workflows, security, approvals, and auditing capabilities already exist, with the help of a dedicated agent team.”
CX requires operational alignment
Many organizations are rapidly adopting AI. However, a successful proof of concept does not necessarily lead to production-ready transformation.
Generative AI can improve content creation and customer interactions, but many organizations still struggle to consistently implement AI across day-to-day operations at enterprise scale, as many tools operate outside of customer operations.
High-quality CX relies on coordinated processes. This means that when AI is disconnected from these systems, it provides recommendations but cannot complete tasks accurately or within business guidelines, resulting in piecemeal automation.
Disconnected AI also raises governance concerns, so these safeguards become even more important as organizations move toward agent-based AI and expect more from technology that performs work securely and transparently.
As a result, improving CX becomes less about deploying another AI interface and more about aligning workflows across the enterprise systems, data, teams, and governance frameworks that ultimately determine customer outcomes.
Oracle’s Fusion AI Play
Oracle introduced an AI-native builder experience in Oracle AI Agent Studio. Enabling customers and partners to create and run Fusion Agentic Application Can be run directly within Oracle Fusion Applications.
These applications combine teams of specialized AI agents that can use Fusion business objects, workflows, approvals, policies, and audit logs to reason and execute work.
To help organizations move AI automation from experimentation to production, Oracle’s approach embeds both the development environment and runtime within Fusion Applications, allowing organizations to build AI capabilities that automatically inherit the platform’s existing models and processes.
Positioning Fusion as both the system of record and the system where AI-powered work is performed expands the scope for building enterprise AI applications.
For example, business users can use no-code and natural language tools, and developers can use a professional coding environment, all within the same managed platform.
By enabling both technical and non-technical users to build AI applications within the same managed environment, Oracle aims to help organizations reduce development bottlenecks and accelerate enterprise AI adoption without sacrificing security or consistency.
Rethinking the value of CX automation
For CX leaders, Oracle’s announcement reflects a broader shift in the way AI creates business value, coordinating multiple activities across business processes to achieve specific outcomes.
AI doesn’t just assist service agents; it improves service by de-escalating and accelerating resolution, and supports revenue operations across customer-facing teams.
This change in the competitive landscape means that enterprises’ AI expectations are focused on business applications where customer, financial, operational, and employee data already exists.
The ability to embed AI directly into these platforms allows AI to access enterprise data, execute workflows, and operate within established frameworks.
In today’s interview with CX, Martin Taylor, co-founder and deputy CEO of Content Guru, said: He argued that successful AI implementation depends on enhancing business processes that organizations have refined over decades.
“CX is built on 40 years of process evolution, and these are business processes that have been honed and evolved since the 1980s, when the first call centers were introduced,” he said.
“We use best-adapted business processes and apply automation to them.”
The challenge for CX leaders evaluating current vendor offerings is to assess where AI can remove friction in the end-to-end customer journey.
Many customer experience problems stem from back-office operations rather than customer interactions, where delays and fragmentation shape the experience.
As a result, organizations must evaluate AI based on its ability to coordinate work across departments and improve measurable business outcomes. Because the biggest opportunity may lie in using managed AI to address the roadblocks that determine loyalty and satisfaction.
