- Developers
- Learn about the practical challenges and surprising customer adoption rates for AI voice agents.
- Business
- Discover how AI voice agents can improve customer service and what knowledge you need to capture for success.
This interview offers a practical, counterintuitive look at AI adoption and customer preference, moving beyond pure technological advancement.
More Customers Chose the AI Agent Than Anyone Expected | Tom Chen, Aircall
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From Subvolts
Summary and analysis by Subvolts editorial, AI-assisted.
Craig Smith interviews Tom Chen of Aircall on AI voice agents. Chen argues AI agents surpass average human reps in customer service due to infinite patience and lower cost. Surprisingly, customers often choose AI over humans, boosting satisfaction. The key challenge for AI adoption is capturing undocumented tribal knowledge from experienced employees, not the AI technology itself.
Companies are using AI for phone calls. Surprisingly, many customers prefer talking to the AI because it's faster and never gets tired. The real trick is teaching the AI the company's secret knowledge, not just the technology.
This episode reveals how AI voice agents are outperforming expectations in customer service. It's for businesses relying on voice communication and anyone interested in practical AI adoption. The conversation highlights how AI's effectiveness hinges on integrating human expertise, a crucial point as frontier labs like Google Gemini and OpenAI develop more sophisticated conversational AI.
- HostCraig S. Smith
- GuestTom ChenChief Product Officer, Aircall
- Guest: Tom Chen, Chief Product Officer at Aircall
- Show: Eye on AI
- Length: 57 minutes
- Customer Choice Finding: More customers chose the AI agent than expected when given the explicit choice, and satisfaction scores increased.
- Key Bottleneck: Undocumented tribal knowledge in long-tenured employees, not AI technology, determines AI agent performance.
Every time you hit a phone tree or a chatbot with canned answers, you're experiencing the gap between what AI can already do and what most companies are still delivering. Craig Smith sits down with Tom Chen, Chief Product Officer at Aircall, to explore why that gap is closing fast, and what it means for any business that relies on voice as a customer communication channel. Tom makes a case that is both practical and counterintuitive: AI voice agents aren't better than your best human rep, but they are better than your average one. They never get frustrated. Their patience is infinite. Their tone never changes. And they can handle 100 concurrent calls at a fraction of the cost of a human operation, without lunch breaks, without bad days, and without going off script.
The conversation covers a finding that should change how any business thinks about AI adoption: when one of Aircall's customers gave callers the explicit choice between a human agent and a faster AI agent, far more people chose the AI than anyone expected, and satisfaction scores went up. Tom also identifies the real bottleneck that most businesses don't see coming: it's not the AI technology, which is increasingly commoditized. It's the tribal knowledge, the undocumented expertise that lives in the heads of long-tenured employees and never gets captured anywhere, that determines whether an AI agent performs well or not. Until that knowledge is surfaced, even the best voice agent will underperform.
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- tribal knowledge
- Tom Chen
- secret or unwritten expertise held by experienced employees
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Questions people ask
- Why are AI voice agents better than human agents?
- AI agents never get frustrated, have infinite patience, maintain a consistent tone, and can handle many calls simultaneously at a lower cost without breaks or deviating from scripts.
- What is the main challenge for businesses using AI voice agents?
- The bottleneck is not the AI technology itself, but capturing and integrating the undocumented expertise, or tribal knowledge, held by long-term employees.
Page generated Oct 19, 2026. Summaries are Subvolts' own; the audio, artwork and notes belong to Craig S. Smith.





