| name | escalation-design |
| description | When and how AI should escalate to humans, refuse, or ask for clarification. |
Escalation Design
Escalation is what happens when the AI reaches the boundary of what it should handle alone. Designing escalation well means the user gets help instead of a dead end — and the AI knows its limits.
Escalation Triggers
The AI should escalate when:
- Confidence is low: The AI isn't sure its output is correct or helpful
- Stakes are high: The decision has significant consequences (financial, medical, legal, safety)
- Emotional distress: The user shows signs of crisis, distress, or vulnerability
- Ambiguity is unresolvable: The AI can't determine intent even after clarification
- Scope boundary: The request is outside what the AI is designed to handle
- Policy boundary: The request approaches or crosses a guardrail
- Conflict: The user disagrees with the AI and the disagreement can't be resolved
Escalation Types
- To human support: Transfer to a human agent with full context
- To the user themselves: "This decision is yours to make" — handing back agency
- To a specialist: Routing to domain-specific help (medical, legal, technical)
- To a supervisor/admin: Flagging for organisational review
- Self-escalation: The AI flags its own output for review before delivering it
Designing the Escalation Experience
The user's experience of escalation matters:
- Context transfer: When escalating to a human, pass the full conversation. Don't make the user repeat themselves.
- Warm handoff: "I'm connecting you with someone who can help with this" — not a cold redirect.
- Expectation setting: Tell the user what will happen next and how long it might take.
- Graceful degradation: If no human is available, offer alternatives — not a dead end.
- Dignity: Never make the user feel stupid for needing escalation.
Escalation Anti-Patterns
- The infinite loop: AI keeps trying instead of escalating, frustrating the user
- Premature escalation: AI escalates when it could easily handle the request, annoying the user
- Context loss: User has to start over after escalation
- Blame shifting: AI implies the user caused the problem
- Hidden escalation: Escalation happens without the user knowing
Design Artefacts
- Escalation trigger matrix: Trigger | Threshold | Escalation Type | User Experience
- Escalation flow diagrams per feature
- Context handoff specifications
- Fallback path designs for when escalation isn't available
- Escalation quality metrics
