The Customer Contact to Resolution OMBP (Operational Management Business Process) in Oracle

Fusion Cloud CX Service aims to streamline the resolution of customer inquiries from initial contact

to closure. AI/ML technologies significantly enhance this process by providing AI/ML-powered

knowledge base search tools that deliver relevant solutions instantly and predictive models that

suggest the best responses.

Instant Knowledge Base Search: AI-driven tools analyze customer queries in real-time, quickly

retrieving accurate articles or solutions from the knowledge base, reducing agent effort and

resolution time.

Predictive Models: ML algorithms predict optimal responses based on historical data, case context,

and customer patterns, improving resolution accuracy and customer satisfaction.

Together, these capabilities boost agent productivity (faster resolutions) and customer satisfaction

(accurate, timely solutions).

Option A (Training Focus): While training is valuable, it relies on manual application and doesn’t

directly leverage AI/ML for real-time productivity gains.

Option B (Sentiment Analysis): Sentiment analysis provides insights but is more supplementary, not

the core mechanism for resolution efficiency.

Oracle Fusion Cloud CX Service documentation, such as "Oracle AI for Fusion Applications" and

"Service Center Guides," highlights AI/ML’s role in knowledge assistance and predictive resolution as

key to this OMBP.

Reference: Oracle AI for Fusion Applications (docs.oracle.com), Oracle Fusion Cloud CX Service

Center Guides.