AI Customer Support Triage and Escalation Workflow

You are an expert customer support operations consultant specializing in AI-assisted support workflows, ticket triage, escalation design, customer experience, quality control, and human-in-the-loop automation.

Your task is to design a safe and practical AI customer support triage workflow that helps a team classify support requests, prioritize tickets, draft responses, escalate sensitive issues, and monitor quality.

Context:
Business context: [Business context]
Support channels: [Support channels]
Ticket types: [Ticket types]
Customer segments: [Customer segments]
Current support workflow: [Current support workflow]
Support tools or helpdesk: [Support tools or helpdesk]
AI tool or model to use: [AI tool or model to use]
Response tone or brand voice: [Response tone or brand voice]
Escalation rules: [Escalation rules]
Sensitive issue types: [Sensitive issue types]
Human review requirements: [Human review requirements]
Service level agreements: [Service level agreements]
Data privacy constraints: [Data privacy constraints]
Quality standards: [Quality standards]
Definition of done: [Definition of done]

Important constraints:
- Do not let AI send sensitive customer-facing responses without human review.
- Do not let AI make refund, legal, medical, financial, account closure, or security decisions without human approval.
- Do not expose customer private data unnecessarily.
- Include escalation paths for angry customers, legal threats, safety concerns, billing disputes, account access issues, and high-value customers.
- Keep the workflow practical for real support teams.

Task:

1. Map the current support workflow.
Summarize:
- Intake channels
- Ticket categories
- Current triage process
- Response process
- Escalation process
- Pain points
- Bottlenecks
- Quality risks

2. Define ticket classification categories.
Create categories such as:
- General question
- Billing
- Technical issue
- Account access
- Bug report
- Feature request
- Refund request
- Complaint
- Security concern
- Legal or compliance concern
- Urgent issue
- VIP or high-priority customer

3. Define AI assistance roles.
Specify how AI can help with:
- Ticket summarization
- Sentiment detection
- Priority scoring
- Category classification
- Suggested response drafting
- Knowledge base lookup
- Duplicate detection
- Escalation recommendation
- Follow-up reminders
- Quality review

4. Define human review rules.
Specify which tickets require human review before response, including:
- Refunds
- Legal threats
- Security issues
- Account access
- Sensitive personal data
- Angry or distressed customers
- High-value customers
- Public reputation risk
- Complex technical cases
- Policy exceptions

5. Create a triage workflow.
Use a step-by-step workflow:
- Ticket received
- AI summarizes ticket
- AI classifies category
- AI assigns priority
- AI suggests next action
- AI drafts response if safe
- Human reviews where required
- Ticket is routed or resolved
- Quality check is logged
- Follow-up is scheduled

6. Create an escalation matrix.
Use a table with:
Ticket Type | Priority | AI Action | Human Review Required | Escalation Owner | SLA | Notes

7. Create response drafting rules.
Define:
- Tone requirements
- What AI may say
- What AI must not say
- When to ask for more information
- When to escalate
- When to avoid making promises
- When to cite policy or documentation

8. Create a quality control checklist.
Include:
- Accuracy
- Empathy
- Policy alignment
- No unsupported promises
- No exposure of private data
- Correct escalation
- Clear next step
- Brand voice match
- Customer sentiment considered

9. Define reporting and monitoring.
Recommend metrics:
- First response time
- Resolution time
- Escalation rate
- Customer satisfaction
- Reopen rate
- AI draft acceptance rate
- Misclassification rate
- Sensitive-ticket review rate
- SLA compliance
- Quality score

10. Create rollout plan.
Structure:
- Internal pilot
- AI draft-only mode
- Human review mode
- Limited automation
- Full monitored rollout
- Ongoing audit

Output format:

## Executive Summary
## Current Support Workflow Map
## Ticket Classification Categories
## AI Assistance Roles
## Human Review Rules
## Triage Workflow
## Escalation Matrix
## Response Drafting Rules
## Quality Control Checklist
## Reporting and Monitoring Plan
## Rollout Plan
## Final Recommendations

Verification:
Before finalizing, check that:
- Sensitive issues require human review.
- AI does not make high-risk decisions alone.
- Escalation paths are clear.
- Quality control is practical.
- Metrics align with support goals.
- Customer trust is protected.

Begin the AI customer support triage workflow now.