Quick Answer
For search, voice, and "just tell me what to do".
AI triage transforms chaotic inboxes into ordered queues by automatically categorizing, prioritizing, and routing support requests based on urgency, customer sentiment, issue type, and customer value. This ensures critical issues get immediate attention while routine queries flow to appropriate channels.
Key Takeaways:
- Not all tickets deserve equal priority
- Sentiment detection catches urgent issues
- Customer value should influence routing
- Category-based routing improves efficiency
- AI triage reduces response time for critical issues
Playbook
Define priority criteria (urgency, sentiment, value, type)
Implement AI classification for incoming requests
Create routing rules based on classification
Build escalation paths for high-priority items
Monitor and refine classification accuracy
Common Pitfalls
- Over-complex priority schemes
- Ignoring sentiment in prioritization
- Static rules that don't adapt
- Deprioritizing customers who become high-value later
Metrics to Track
Time to first response by priority
Classification accuracy
High-priority resolution time
Customer satisfaction by priority tier
FAQ
How do I balance efficiency with fairness in triage?
Set maximum wait times even for low-priority queues. Prioritization should speed up urgent issues, not abandon routine ones. Fair baselines with acceleration for urgency is the right model.
Related Reading
Next: browse the hub or explore AI Operations.