“Hello, AI Speaking. How Can I Help You?”

Although playful by design, the title of this article is more accurate than many people realize. Today's contact center is driven by artificial intelligence (AI) to create a hyper-personalized experience that leverages customer and employee data to provide a predictive and prescriptive customer journey. In fact, over the last few years, 23 percent of organizations have integrated AI into their contact centers. And among them, 73 percent introduced AI in the past year. Why is the phone suddenly ringing off the hook for AI-based service-operation optimization? According to Forbes, it's the explosive growth of widely available cloud services and machine-learning tools that have put powerful new AI capabilities in the hands of call centers to improve customer service in all forms.

The timing for AI to be fully embraced in contact centers could not be better. In March , Indeed, a subsidiary of Japan-based Recruit Co., had almost 75,000 job openings within call centers that can't be filled fast enough. Zendesk underscores this issue in its Customer Experience Trends Report by stating, "Use of AI becomes paramount because 42 percent of customer service leaders expect requests to grow, whereas just 36 percent expect to be able to expand headcount. This gap represents the sweet spot where AI can help."

AI Is the New Operator Assistance

When applied to a contact center, in its simplest terms, AI is an inference engine built and trained to recognize patterns and suggest activities or actions. These traits are ideal for applying to intelligent quality assurance calls, where historically calls are randomly recorded for quality purposes to find out how well agents did or didn't do. The ongoing issue with recording calls is that this only enables companies to evaluate the customer experience after the call is completed—it does not prevent a frustrating experience from occurring while on the call. And there are still contact center methods with which AI is currently assisting.

AI chatbots are already in more common usage than many customers realize. Most customers looking to get a question answered quickly won't bother to call in and deal with dreaded hold times. Instead, they'll head right to the company's website and interact with a chat agent. While it seems more effective to have actual people interacting with customers, this can quickly consume resources and reduce the productivity of your team. Automating replies to the most common customer questions will free up time for agents to concentrate on customer concerns that require specific person-to-person interaction. The net goal of any customer interaction is to prevent a frustrating experience, and in this particular area, AI holds tremendous promise.

AI in the contact center promises to equip agents with guidance toward the next-best action in real time and possibly without agent interaction at all. This requires two things: a well-tuned inference engine and a ton of processing power.

AI also improves the efficiency of the contact center by enabling the analysis of enormous data sets. Its data resources give companies back time to focus on more human tasks. The rule-of-thumb is what's time-consuming for a human can be done more quickly, easily, and accurately by AI.

AI-enhanced centers will become more commonplace as the price of processing power decreases and bandwidth increases.

Over the years, industry-leading communications platform companies have acquired AI and proactive conversation technologies to predict customer usage patterns (e.g., how they resolve problems and where they tend to look for answers. In addition, some of these communications platforms support 30 channels simultaneously: voice chat, SMS, and social media (e.g., Twitter, Facebook, Instagram, WhatsApp), and can contact-switch from one to the other. This empowers companies to seamlessly interact with their customers based on needs and communication preferences.

Perhaps most impressive of all, these solutions can also provide sentiment analysis that determines if customers were upset or happy (i.e., speaking loudly or quickly) and then takes this a step forward by identifying specific words or trends. They can also determine if customers needs live interaction to de-escalate the experience based on voice tonality, the words they use, or their pitch.

Is There Anything Else I Can Assist With?

Ensuring a good customer experience can be complex, but it does not have to be complicated. The key to ensuring a successful contact center is not only evaluating context from the dialogue but also leveraging AI to guide conversations to better, more helpful customer experiences in the first place. Contact centers that have enabled AI to become their first line of communication are receiving notable results in customer satisfaction (they get to interact in their preferred methods) while also finding a means to circumvent the open headcount gap.

Luis Camacho is a senior consultant at Anexinet.