Executive Summary

This checklist is designed for business and technology leaders seeking fast, measurable improvements in contact-center performance using Amazon Connect AI.
It focuses on practical applications that reduce handle time, improve first-contact resolution, and increase agent effectiveness — without risking customer experience.

10 Places AI Improves Metrics Fast

• Intent detection & intelligent routing
• Real-time AI Agent Assist
• Knowledge base search (RAG)
• Auto-summaries and disposition notes
• Automated QA scoring
• Call reason classification
• After-hours self-service automation
• Multilingual understanding
• Predictive intent nudging
• Narrow-scope self-service containment

What NOT to Automate (Yet)

• Escalations and complaints
• Billing disputes and refunds
• Edge-case troubleshooting
• Policy interpretation
• High-emotion or high-stress calls
• Conversations requiring explanation or judgment

Common Mistakes

• Treating AI as a bot replacement instead of a performance tool
• Skipping prompt and guardrail design
• Over-automating before understanding call drivers
• No baseline metrics or ROI hypothesis
• Training AI on outdated or messy knowledge content
• Relying on vendor demos instead of real call flows

AI Readiness Checklist

• Top call drivers identified
• Clean and current knowledge base
• Defined success metrics (AHT, FCR, CSAT)
• Structured Amazon Connect flows
• Human fallback paths
• Prompt governance and guardrails
• Business and IT alignment

DrVoIP — Where IT meets AI — in the cloud.