Rethinking AI in Customer Service: When It’s Not the Right Fit

In today’s business landscape, the allure of Artificial Intelligence (AI) has many companies clamoring to integrate it into their customer service departments. However, as the CEO of a voice AI company, I often caution potential clients against jumping on the AI bandwagon without careful consideration. My sales team may think I’m off my rocker, but my experiences leading AI implementations across various businesses indicate that using AI indiscriminately can result in more trouble than it resolves.

Recently, a law firm approached us with hopes of automating their client intake calls through AI. After reviewing their call recordings, I promptly advised them against it. The nature of their inquiries involved sensitive legal matters, emotional nuances, and complex assessments. Allowing AI to manage these interactions would likely backfire, leading to significant client dissatisfaction.

This scenario is far from isolated. The current hype surrounding AI has created a perception that every business should adopt it, and immediately. The truth is that AI excels in certain contexts but can falter drastically in others.

Key Considerations Before Implementing AI: The Three Essential Checks

Before diving into AI, here are three critical criteria your business must evaluate:

1. Do Your Calls Follow Predictable Patterns?

From my analysis of over 10,000 customer call transcripts across various industries, I’ve found that some businesses see as much as 80% of their calls revolve around a handful of common topics—appointment scheduling, FAQs, straightforward troubleshooting, and status updates. These repetitive patterns serve as ideal candidates for AI integration.

On the contrary, if your calls are unique and varied, it’s time to pause. For instance, a mental health clinic we assessed had individualized conversations where every caller had a distinct and intricate situation. In such cases, AI would likely prove detrimental, not beneficial.

To aid our clients in this area, we developed a pattern analysis tool that evaluates call transcripts. If less than 70% of your calls demonstrate recognizable patterns, it’s a sign that AI isn’t geared for your needs. A home services client discovered that 85% of their calls were simply appointments, making them excellent candidates for AI. Meanwhile, a B2B software company found that only 30% of theirs followed recognizable patterns, indicating a need for human interaction.

2. Have You Established Clear Escalation Triggers?

For AI to succeed, it is crucial to define what constitutes a failure. I observed one organization that