It’s easy to miss the mark with customers when their demands are constantly shifting. But despite all the changes, one thing has remained consistent: Expectations are always rising. In fact, according to recent PolyAI data, 88% of customer service and CX leaders believe customer expectations have increased in the last year — particularly around the desire for immediate responses and more knowledge and guidance from advisors.
Though customers expect more than ever, many traditional customer service methods aren’t working anymore. Advanced voice AI is emerging as a frontrunner solution to meeting these heightened customer needs and desires.
Voice AI, like early versions of Siri, initially struggled to live up to the hype. Nascent voice AI technologies were only capable of single-turn conversations and often produced frustrating misunderstandings. Now, however, the tech has evolved to a whole new level, where it can enhance customer service capabilities and improve experiences for all involved.
The benefits of voice AI for customer service
Customers calling for service don’t want to wait to speak to an agent. They definitely don’t want to be tasked with navigating a confusing menu tree that ultimately loops them back to where they started — they’ll just hang up instead. Unfortunately, their impatience doesn’t end there: Even once they are connected with an agent, the likelihood of them being frustrated is high, and human CS agents often receive the brunt of that frustration.
AI agents powered by sophisticated Spoken Language Understanding (SLU) capabilities, machine learning (ML) and Large Language Models (LLMs) can help mitigate these challenges.
AI agents are available 24/7, so callers can reach out whenever they want. AI agents are easier to deploy in large numbers, so you can bid long hold times farewell. AI agents can also act as the first line of defense against an agitated customer, working to defuse the situation and shield live agents from verbal abuse. Additionally, the AI agent communicates with such natural-sounding responses, some callers may initially mistake it for a human agent, especially since this technology has been developed to take conversational context into account.
Context is key when it comes to producing human-like interactions that center on empathy and conversational nuances. The best AI agents don’t just process what words were said, they also understand the meaning behind the words, even when customers tell long, winding stories. This ability to accurately understand and parse a conversation is one of the biggest differences between modern voice AI and those earlier trailblazers, like the original 2010 version of Siri. Some of the biggest complaints about Siri in its early days were that it struggled to comprehend what question was being asked, especially if the speaker had an accent, and that it would, in turn, produce inaccurate results.
Modern AI agents can interpret spoken language much more accurately, asking clarifying questions and engaging in intelligent discussion, delivering empathetic responses that foster trust. In some instances, it’s important that customers can get through to a human rep. Maybe they have a life-threatening medical problem, or they simply don’t want to engage with AI. Building trust with customers means knowing when to hand a call to a person, and today’s leading AI agents are well equipped to do that both intelligently and seamlessly.
Emphasizing empathy
Empathetic AI agents do more than just “hear” customers — they actually listen and adapt their responses accordingly, understanding customers’ needs at a much higher level than legacy voice technologies, such as IVR systems. Voice AI can improve the overall customer experience through its ability to create natural interactions via emotional recognition and conversational contextualization. It can even understand when a call might be better handled by a human agent to deliver the best possible experience to every customer.
Here’s a deeper look into how these capabilities improve the customer experience:
- Response adaptation. Since AI agents have the ability to adjust their tone and tactics in real time, they can be more empathetic in emotionally sensitive situations. That means these kinds of interactions are no longer off the table for AI. Some customers may even find that these types of delicate conversations are actually less emotionally taxing to have with an AI agent than with a human. That further increases customers’ comfort communicating with voice AI.
- Understanding conversational nuance. Natural language conversations don’t always follow a linear, formulaic structure. For example, a customer may remember an important detail while an AI agent is talking about something else and interrupt the AI in the middle of a sentence. With an IVR system or chatbot, an interruption could derail the conversation entirely, but fine-tuned voice AI systems can take these types of conversational anomalies in stride. An AI agent can resume where it left off after being interrupted, knows to remain silent during a natural pause in conversation, understands callers regardless of accent or dialect and can even make inferences about what else a caller may need. These features enable customers to communicate naturally, reducing friction and galvanizing their confidence that the AI can solve their problems.
- Human handoff. Today’s AI agents can handle even complex customer service transactions, but some conversations still benefit greatly from a human touch. Consider a healthcare practice where registered nurses are trained to listen out for distress, even when the caller doesn’t explicitly mention it, or the customer who has had one too many bad experiences with low-quality voice automation and just wants to speak to a person. In these instances AI agents know to transfer the call to a human agent as soon as possible to get a faster, more accurate resolution for the customer.
Empathetic voice AI is the future of customer service, not because it’s replacing humans, but because it can improve humans’ experiences — on both ends of the phone. Human agents’ workloads will be lighter, and customers will be able to access the service they need faster and more efficiently.
As customer expectations continue to rise, CS teams that implement intelligent voice AI will be better equipped to meet (and exceed) those expectations, driving sustained, future-proofed customer satisfaction.
