
Overview
Prerequisites
- Microsoft 365 licence with Copilot Studio access
- Documented list of your top 20 citizen enquiry types
- Approval from your entity's IT security team
- At least one SME from each service area for knowledge review
Step 1: Service Taxonomy Design
Before building anything, map your service landscape:
- Pull the last 6 months of citizen enquiry logs
- Categorise by topic and sub-topic
- Identify the top 20 enquiry types that make up 80% of volume
- For each: document the answer, the process, and escalation conditions
Step 2: Knowledge Base Preparation
- Write FAQ documents for each service topic (plain language, short answers)
- Upload to a SharePoint knowledge library
- Include: eligibility rules, step-by-step processes, required documents, timeframes
- Review for accuracy with service owners — chatbot quality = knowledge quality
Step 3: Build in Copilot Studio
- Create a new agent in Copilot Studio
- Connect to your SharePoint knowledge library
- Define conversation topics for each service category
- Build escalation flows (human handoff via Teams or email)
- Test with 50 real citizen enquiries across all topics
Step 4: Governance & Compliance
Before go-live, ensure:
- No personally identifiable information (PII) stored in conversation logs
- Clear disclosure that user is interacting with an AI
- Arabic language support tested
- Accessibility tested (screen reader compatible)
- TDRA compliance checklist completed
- Legal sign-off on chatbot response liability
Step 5: Launch & Iterate
- Soft launch with internal testers for 2 weeks
- Monitor fallback rate (target < 15%)
- Review unresolved queries weekly and add to knowledge base
- Run quarterly service reviews with SMEs
Key Performance Indicators
| KPI | Target |
|---|---|
| Automation rate (first contact) | > 75% |
| Average response time | < 3 seconds |
| Citizen satisfaction score | > 4.0/5.0 |
| Escalation rate | < 20% |
| Chatbot uptime | > 99.5% |