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

As the founder of a voice AI company, I often find myself in a peculiar position: advising potential clients not to invest in our technology. While this might appear counterintuitive to my sales team, it stems from my extensive experience working with diverse organizations. What I’ve learned is that hastily integrating AI into customer service can exacerbate issues rather than resolve them.

Take the recent example of a law firm that sought our assistance for managing client intake calls. Upon reviewing their call recordings, I immediately recognized they were not equipped to implement AI effectively. Their intake process involved complex legal inquiries and emotional discussions related to traumatic experiences, making an AI-driven solution ill-suited for their needs.

This isn’t an isolated case. The growing excitement around AI has led many businesses to believe they desperately need it, often overlooking the specific conditions under which AI can be beneficial. The reality is that while AI is a remarkable tool for certain applications, it can also prove to be disastrous in others.

Before jumping on the AI bandwagon, here are three critical criteria your business should evaluate:

1. Are Your Calls Predictable?

In analyzing data from over 10,000 customer interactions across various industries, it became clear that successful AI implementation largely hinges on the predictability of conversations. In some sectors, as much as 80% of calls revolve around a few common topics—such as scheduling, frequently asked questions, and basic troubleshooting. These scenarios are ideal for AI.

However, if your customer interactions are varied and complex, think again. For instance, one mental health clinic we assessed found that every call presented unique situations that required empathy and active listening. In these contexts, AI could do more harm than good.

To help assess the suitability of AI for your business, we developed a pattern analysis tool that examines your call transcripts. If fewer than 70% of your calls follow recognizable patterns, AI may not be the right choice for you.

2. Do You Have Defined Escalation Triggers?

Implementing AI without clear rules for escalation is risky. I’ve seen companies deploy chatbots that fail miserably because there were no guidelines on when to transfer calls to human agents. This resulted in increasingly frustrated customers being stuck with an inadequate AI, leading to a poor experience.

Before considering AI, it’s essential to establish precise criteria for escalating interactions to a human representative. These criteria can include specific phrases, sentiment