Contact Center Generative AI: Perspective from a Distinguished Professor

Talk about Generative AI continues to run rampant, but if there’s one thing for sure: There are few actual experts who can not only provide the historical context of this moment, but also a forward-looking perspective.

That’s why we brought in L.J. Skaggs Distinguished Professor and Executive Director of the Retail Management Institute at Santa Clara University, Kirthi Kalyanam to speak during our GPT Innovation Day.

Here are the highlights from the wide-ranging conversation:

Q: Can you put Generative AI and this moment in context for us?

Professor Kirthi: If you look at this 30 year history, you repeatedly see the same phenomenon play out again and again. A new technology comes around and some company takes it to solve a customer experience problem that has not been solved before. And it's sometimes just amazing how obvious that is. We’re having one of those moments now.

Q: What are some examples of this?

Professor Kirthi: Chewy is in the pet business. A lot of pet owners are not pet owners. They're pet parents. They don't use the outsource calls at Chewy. Somebody picks up the phone. It's one of their employees and it's their own call center. They created this huge space in that industry, which others have not been able to. That's how they build the connection.

Q: What’s your takeaway from Chewy’s approach to customer service?

Professor Kirthi: The bottom line is that there's many, many industries where the customer experience is an important white space that is not properly addressed with the existing incumbents or with the existing technology. And there's huge returns to that payoff. Chewy is selling the same product that Petco is selling and pet smart selling. Nothing unique about the product carriers. It's purely a better customer experience.

Q: So how does Generative AI fit into this story for you?

Professor Kirthi: I see Generative AI as a way for all of these companies to truly start creating differentiation in that high involvement purchase. The reason we haven't done more of this is that high involvement servicing is always using humans, and there's a huge cost to that. It affects your cost and your P&L, and it hasn't been something you can do very well. So I certainly expect to see more blending of technology with humans.

Q: How do you think this will change consumer expectations?

Professor Kirthi: I think people are going to value authenticity more than anything else. If generating content is as easy as it has become with ChatGPT, consumers are pretty quickly going to see that a lot of this content is not real. And so then the question is, where can you create authenticity, where you can create emotion, where you can create trust. These parameters are gonna become very critical.

Q: How do you think ChatGPT will negatively affect customer experience?

Professor Kirthi: The first negative effect of ChatGPT is going to be an erosion of trust and content. I agree. Dramatic erosion of trust in any kind of content, whether it's written content or images.

Q: How should contact centers think about Generative AI and GPT?

Professor Kirthi: Businesses are going to have to double down in figuring out how this will affect their business. That's the first check box. If you don't have that very cleanly lined up, this new wave of technology is going to cause a lot of confusion. The second question I would ask is “What's my strategy to have an emotional connection and continuous emotional conversation with the customer?” because Generative AI is going to begin commoditizing experiences. Technology commoditizes, but it also differentiates. It all depends on whether you know how to use it and which way you use it.

Q: What is your recommendation for contact center leaders interested in Generative AI?

Professor Kirthi: Thank goodness Open AI released ChatGPT in the public domain. Enterprises don't really have to sell this idea to their board anymore. The board is asking them “What does this mean for us?” So I think this is an opportunity, not a problem.

The second thing is that this technology is highly triable. You don't have to make a major investment to try it out. You already have platforms available and it's easy to build an entry point to start looking at a high value case study immediately.

Find those investments that are easy to do that are completely reversible. That way, you’re moving along, moving quickly.