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Controversial Opinion – The Majority of Companies Should Avoid Implementing AI in Customer Support

Why Many Businesses Should Reconsider Using AI for Customer Service

As a leader in a voice AI company, I often find myself advising potential clients against investing in our technology. This might seem counterintuitive, especially to my sales team, but after witnessing the implementation of AI across numerous organizations, I firmly believe that forcing AI into unsuitable scenarios can lead to more challenges than solutions.

Take, for instance, a law firm that approached us last month with the goal of utilizing AI for client intake calls. After reviewing their call recordings, I recognized that their intake process was fraught with complex legal inquiries, emotionally-charged conversations, and intricate eligibility assessments. Employing AI for such sensitive interactions would likely have resulted in disaster.

This situation is not uncommon. The current excitement surrounding AI has led many businesses to believe they need to incorporate these technologies immediately. However, the truth is that while AI excels in specific contexts, it can falter dramatically in others.

Before considering the implementation of voice AI, here are three critical criteria every business should evaluate:

1. Do Your Calls Follow Predictable Patterns?

Through an analysis of over 10,000 customer call transcripts across various sectors, I’ve identified that in some businesses, up to 80% of interactions revolve around a handful of familiar topics: appointment scheduling, FAQs, status inquiries, and basic troubleshooting. These scenarios are well-suited for AI.

On the flip side, if your calls are inherently diverse and unique, it may be best to hold off. For example, a mental health clinic we assessed found that every call presented a distinct challenge, demanding empathy and careful listening. In such cases, AI could complicate rather than facilitate communication.

To determine if your calls exhibit recognizable patterns, we developed a pattern analysis tool. If less than 70% of your conversations fall into predictable categories, it’s a sign that AI may not be the right fit for you. We had one home services client discover that 85% of their calls were simply booking appointments, making them ideal candidates for AI. Meanwhile, a B2B software firm found only 30% of their calls were consistent—indicating a need for human interaction.

2. Are There Clear Escalation Protocols?

AI systems must be equipped with well-defined escalation protocols to gracefully manage failures. In one instance, I observed a company deploying a chatbot without any escalation parameters. The bot became increasingly ineffective as it attempted to assist frustrated customers who were requesting to speak with a

One Comment

  • Thank you for sharing such a thoughtful and nuanced perspective on AI implementation in customer support. I appreciate the emphasis on evaluating whether your specific call patterns align with AI’s strengths before rushing into adoption. Indeed, AI truly excels in handling predictable, routine interactions, but as you’ve highlighted, its limitations become apparent when dealing with complex or emotionally sensitive conversations.

    One point worth considering is the importance of blending AI with human support rather than choosing one exclusively over the other. By implementing AI for repetitive tasks—like appointment scheduling or FAQs—you can free up human agents to focus on more nuanced, empathetic interactions that require critical thinking and emotional intelligence. Additionally, establishing clear escalation protocols, as you mentioned, ensures that customers are seamlessly transitioned to human agents when needed, enhancing overall support quality.

    Ultimately, a tailored approach that respects the nature of your customer interactions and focuses on augmenting human effort can lead to smarter, more effective service strategies. Thanks again for sparking this important discussion!

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