Rethinking AI in Customer Service: Why Some Businesses Should Hold Back

In the fast-evolving landscape of technology, Artificial Intelligence (AI) has quickly become a buzzword in the business world. As the CEO of a voice AI company, I often find myself at odds with my sales team. Surprisingly, I frequently advise potential clients to reconsider buying our product. After working with various businesses across different sectors, I’ve learned that the inappropriate application of AI can lead to more problems than solutions.

Recently, a law firm approached us with the intent of utilizing AI for handling client intake calls. After reviewing some of their call recordings, I advised them that they were not yet prepared for such an implementation. Their intake process was rife with nuanced legal questions, emotional callers recounting traumatic experiences, and intricate eligibility evaluations—elements that AI struggles to navigate effectively. An AI system in this context would likely have resulted in significant miscommunication and client dissatisfaction.

The truth is, the hype surrounding AI can mislead many companies into believing that they must adopt it immediately. However, AI excels in targeted applications while failing dramatically in others. So, how can businesses determine if they are ready for voice AI? Here are three essential criteria to evaluate before considering its application in customer service.

1. Are Your Calls Predictable?

After analyzing the transcripts of over 10,000 customer calls across various industries, I found that many businesses have calls that largely adhere to a few standard conversations—think appointment scheduling, frequently asked questions, or basic troubleshooting. In businesses where 80% of calls can be categorized into just a handful of types, AI can be extremely useful.

Conversely, if each incoming call varies significantly, it’s best to reconsider AI integration. For instance, a mental health clinic we assessed had no two calls alike, with each patient presenting complex and personal situations requiring empathetic listening—areas where AI would struggle, if not fail entirely.

We developed a tool that performs pattern analysis on call transcripts. If your calls show less than 70% consistency in patterns, it’s a sign that AI may not yet be suitable for your operations. One home service provider found that 85% of their calls involved straightforward appointment bookings, marking them as ideal candidates for AI. In contrast, a B2B software company had only 30% of their calls fitting a predictable pattern, emphasizing their need for human engagement.

2. Have You Defined Escalation Triggers?

Proper implementation of AI requires