Quick Answer
For search, voice, and "just tell me what to do".
Every time a support agent switches between different issue types, systems, or customers, they lose time and mental energy rebuilding context. AI eliminates this by handling routine queries, batching similar issues, and providing instant context for each interaction.
Key Takeaways:
- Context switching costs 15-25% of agent time
- Similar issues should be batched when possible
- AI can provide instant context for each interaction
- Specialization reduces switching
- Flow state improves quality and speed
Playbook
Analyze context switching patterns in support workflow
Implement AI to handle interruptive routine queries
Design routing for issue type batching
Create context summaries for each interaction
Protect focused work blocks for agents
Common Pitfalls
- Ignoring the cost of switching
- Random distribution of different issue types
- No context persistence between interactions
- Interrupting agents for routine queries
Metrics to Track
Context switches per hour
Time to full context per interaction
Quality by issue type batching
Agent flow state duration
FAQ
Is specialization better than generalization for agents?
A hybrid approach works best: some specialization reduces context switching, but cross-training maintains flexibility. AI handling routine queries allows agents to develop deeper expertise in complex areas.
Related Reading
Next: browse the hub or explore AI Operations.