Over the past two decades, the contact center industry has promised capabilities that will significantly improve customer experience.

This is important because CX is now the top brand differentiator, with many consumers switching loyalties because of a single bad experience. Though it’s true that the contact center providers have delivered new capabilities such as omnichannel communications, self-service tools and more, consumer satisfaction with contact centers remains low.

One of the big frustrations for consumers is when they engage with a contact center to conduct business online or through an automated system but discover they need help from a human. Sometimes the transition from machine to human is bumpy, as there are cases when the agent needs to know what the customer is trying to accomplish. Another issue is when the customer is required to start over. Whatever the reason, despite years of promise, contact center interactions do not deliver experiences that delight.

Generative artificial intelligence is rapidly becoming more sophisticated and a significant factor in how businesses engage with customers. But can gen AI make contact center interactions more effective — and less frustrating? I discussed this with Jonathan Rosenberg, chief technology officer and head of AI for Five9 Inc., one of the leading cloud-based contact center solutions providers.

Rosenberg firmly believes AI has reached the point where profound improvements will soon be made in how people engage with businesses. “The future of CX is that generative AI will allow us to reconverge the online digital experience and calls with customer service professionals,” he said. “It will be the best of both worlds, where your experience with a brand is always conversational.”

How gen AI can improve the online customer experience

Before the internet, making travel arrangements, for example, typically involved calling a travel agent. That agent had all the information on airlines and hotels and knew how to obtain a good deal for the customer. It was easy to ask questions and get good advice to maximize your travel experience.

Sitting at a laptop and scrolling through all the options for flights, hotels, rental cars and the like removes human expertise from the process. But what happens if you have questions or get stuck and can’t complete an online transaction? You click the “help” button and hope for the best.

Will you be connected to an informed specialist who can assist you? Or will you have to restart the process from scratch, wasting time and testing your patience? That’s where the convergence of humans and gen AI happens.

“A human can be brought in to close the deal,” Rosenberg explained. “The role of the agents in this model becomes AI-assisted observation of the CX involvement, still sometimes reactively but often proactively, to close deals or creatively support the customer. When we do that, we can eliminate hold times because the system knows this interaction is reaching a point where a person better be brought in. And gen AI can cue the customer that a human agent is joining the call, even before they press the call button.”

Rosenberg refers to call centers as “the industry that software forgot.” By that, he means it’s perhaps the first industry you think of that makes software disliked by everyone who uses it. That’s where gen AI is starting to change the game for customers and call center agents.

“The new AI-driven model will function as if you’re always chatting with the contact center; it’s just that sometimes a human joins in,” he said. Rosenberg explained that when an agent joins the session, “they’ve already looked at the history of this thread.”

He compares it to a consumer being able to look back at a long text chat on a service provider’s website. They can scroll back to see what was said earlier to keep the discussion on track. It’s the same when AI hands off the call to a live agent. “When a human is brought into the loop, they see the information you’ve been sharing with the system,” he said. “AI summarizes it so the agent instantly knows what you’ve been doing. We’ve been trying to solve this problem in the contact center industry forever.”

Making the AI vision a reality

Rosenberg calls the computer/human collaboration he described “the vision.” The hard part, he said, is the path to get there: “We’re starting down the road of building these gen AI conversational experiences.” The key is to smoothly and efficiently integrate all of the information from an online customer experience and an interaction with a human agent into a seamless whole.

The goal is to create a smooth experience for the customer and the contact center team. Today’s chatbots deployed by airlines and other CX businesses are a big first step toward this goal. When gen AI begins to play an even more prominent role, he said, “you’ll still have your web elements — your cart, your payment screens — and you’ll have to input your credit card number. But it all will be integrated into a conversation.”

Rosenberg added that “you can’t go there overnight. We’re going to start by making multimodal gen AI-powered bots that can be segmented in the website and grow in their capability over time until customers and users feel confident they work well enough to get us to the vision I described.”

Gen AI-driven ‘hyper-personalization’

“Imagine that when a user is transferred to an agent, a little piece of software looks up your billing records, last product orders, and past 10 conversations with the brand and produces a one-paragraph summary for the agent,” he described. “That starts to deliver this hyper-awareness and personalization we’ve never been able to do in a contact center because we didn’t have the gen AI technology that could be given access to all this data and create concise summaries that could power this experience. Now we can.”

That, he added, “becomes an ingredient. The way to think about it is that as we work toward this vision, which can be composed of these individual ingredients. We’ll build those ingredients and allow them to be used much faster, working us and our customers toward this ultimate vision.”

Where does customer data reside in a gen AI environment?

In Rosenberg’s vision, “The role of the contact center is ultimately an integrator and an orchestrator that goes in and accesses all those systems that have data about the consumer. It provides the front door for the customer to interact with the brand and how human beings support those customers to interact with the product.”

With that “front door” comes a tremendous responsibility to secure customer data. Rosenberg says that for Five9, protecting sensitive data “has been in our DNA since the beginning, and we’re going to continue to do it.”

Ultimately, gen AI is a tool to generate more business

“For any brand, what’s the purpose of their online experience?” he said. “It’s to drive revenue. Even if a company isn’t conducting e-commerce transactions, the website’s purpose is to drive revenue.”

It’s a multi-year vision, he noted. “Any brand today with an online or mobile experience that they use to generate revenue through e-commerce or lead gen will want this,” Rosenberg said. “That’s healthcare, financial services, travel, retail and entertainment. You’d be hard-pressed to find something not in that category.”

As Rosenberg sees it, contextual data is the superpower of gen AI. “Contextual data is the gold in the era of generative AI,” he said. “The AI can take your mortgage application, the history of all your business with the bank, and everything you did on the website. It can be fed into the contact center in real time so the brand and the agents can deliver the personal experience people require. We couldn’t do this until gen AI. It finally allows us to deliver on the promise contact centers have failed to deliver on for many years.”

Summary

The contact center is the most mercurial of all the industries I track. For the past decade, the vendor community has rolled out new feature after new feature, giving brands a wide range of ways to interact with their customers.

However, it’s also true that, as Rosenberg explained, customer frustration remains high as the processes remain people-dependent, and with more channels comes more data, and the ability for humans to keep up quickly vanishes.

Rosenberg is bullish that gen AI can close this gap, and I am too. It’s the missing piece that can turn data into insights, enabling brands to connect with consumers quickly and in a highly personalized way.

Zeus Kerravala is a principal analyst at ZK Research, a division of Kerravala Consulting. He wrote this article for SiliconANGLE.

Image: SiliconANGLE/Ideogram