Case Study 03
AI & Support Automation
Piloted conversational AI and automation workflows to evaluate opportunities for faster resolution, smarter routing, and more efficient support.
- Conversational AI
- Workflow automation
- Intelligent routing
- Knowledge management
- AI-to-Human handoffs
- Automation performance evaluation
Customer Contact
AI Triage
Resolution or Human Transfer
- Resolution
- Human Transfer
Follow-Up
The Challenge
Conversational AI needed to be evaluated against the realities of complex technical support. Answering a call was not enough: interaction quality, unresolved issues, transfers, and customer hang-ups could reveal where automation added friction rather than value.
The Approach
I evaluated AI-assisted phone interactions to identify where the AI agent provided value and where human support remained necessary. The objective was not simply to replace agents or reduce call volume, but to improve the customer experience and reduce unnecessary work. I used observed performance to guide a phased approach to expansion.
What Was Implemented
- I reviewed resolution rates, transfers, customer hang-ups, and interaction quality to assess the conversational AI pilot.
- I analyzed which interactions suited automation and which required human judgment or deeper technical support.
- I improved knowledge quality and conversation routing, including AI-to-Human handoffs when callers needed live Support.
- I used pilot findings to guide a phased approach to expanding automation based on demonstrated usefulness.
Results & Learnings
The pilots helped identify the limits of conversational AI in complex technical support environments and the importance of well-defined use cases.
The findings informed a more targeted approach to knowledge management, routing, and AI-to-human handoffs.
- Automation should expand because it proves useful, not because the technology makes it possible.
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Data-Driven Leadership