Rethinking AI in Customer Service: When to Embrace or Avoid Automation

As a leader of a voice AI company, my perspective on Artificial Intelligence in customer service may surprise some: I often advise potential customers not to purchase our solutions. While my sales team might see this as counterproductive, my experiences have shown that hastily integrating AI into customer service can lead to more issues than it resolves.

For example, a law firm recently contacted us, eager to implement AI for their client intake calls. After reviewing their call recordings, I concluded they weren’t ready for such a drastic change. Their intake process was filled with complex legal inquiries, emotional discussions, and sensitive assessments. Employing AI in such a scenario could easily result in disastrous outcomes.

This situation is not unique. The current enthusiasm surrounding AI has led many businesses to believe they urgently need these technologies. However, we must recognize that AI excels in specific domains while faltering in others.

Three Essential Criteria for Introducing Voice AI

Before even considering voice AI, there are three critical questions your business should address:

1. Are Your Calls Patterned Predictably?

Through my analysis of over 10,000 customer calls from various sectors, I discovered that many businesses see as much as 80% of their interactions boil down to a handful of similar topics, such as appointment scheduling, FAQs, and basic troubleshooting—all of which are ideal candidates for AI.

Conversely, if your calls are unique and varied, you should reconsider. For instance, a mental health clinic we assessed had no two calls alike; each involved intricate personal histories that required empathy and nuanced listening. In such cases, AI would likely hinder rather than help.

We’ve developed a pattern analysis tool that evaluates your call transcripts. If less than 70% of your calls align with recognizable patterns, it’s time to hold off on AI integration. A home services company, for example, found that 85% of their calls involved straightforward appointment bookings, making them prime candidates for AI. Meanwhile, a B2B software firm determined that only 30% of their conversations followed predictable patterns, indicating they needed human agents.

2. Have You Established Clear Escalation Triggers?

AI technologies can only fail gracefully if you have criteria in place for what failure looks like. In one instance, a company adopted a chatbot without any escalation protocols. Frustrated customers found themselves repeatedly stuck trying to get assistance from a bot instead of a human, leading to