ai-pocalypse AI will not replace the people in the call center, but it will rejigger the software stack to make agents more capable of solving customer issues without the need to swivel-chair into multiple systems or escalate complaints, said Vasili Triant, CEO of UJET.
“The problem actually is the systems themselves, not the humans. It’s what the humans have to deal with,” Triant said. “So we believe AI has a huge, huge implication and impact on the customer experience base. We just believe it’s going to happen a different way than all the messages happening today. So instead of the ROI being ‘I’m going to remove humans.’ Your ROI becomes ‘I’m not spending money on a legacy application that doesn’t need to be there anymore.’ “
UJET is a cloud platform that uses automation and AI to improve a call center agent’s ability to solve customer problems and provides its customers with call center data tracking and analytics. Its customers include wellness brand GNC, shoemaker Alto, cookware brand Lodge, and the point-of-sale platform Zettle.
The notion that emerging AI capability will replace call center employees has been touted by Tata Consultancy Services and by startups such as LimeChat, but they don’t account for the massive amount of automation that has already happened over the last 30 years as corporations have given customers self-service abilities around bank balances, wire transfers, billing, reservations, and password resets, Triant said.
“There’s a lot of companies that have already tried doing the body replacement, like companies that we’re even dealing with, and they’re like, ‘Okay, we put this stuff in. We ramped it all up,'” he said. “It does some good simple things, but it’s not replacing the body, like the ROI is not panning out on that stuff.”
Two weeks ago, Gartner released a report saying that by 2030 the cost per resolution for generative AI in customer service will exceed $3, higher than the cost of many B2C offshore human agents. Analysts attributed the increase to rising data center costs, a pivot from subsidized growth to profitability among AI vendors, and increasingly complex use cases that consume more tokens and require expensive talent.
“Customer service leaders are determined to use AI to reduce costs, but return on those investments is far from guaranteed,” said Patrick Quinlan, senior director analyst in the Gartner customer service and support practice. “Full automation will be prohibitively expensive for most organizations; instead, leading organizations will use AI to drive customer engagement rather than to cut costs.”
Gartner also predicts that by 2028, regulatory changes related to AI will increase assisted service volume by 30 percent.
“Regulations mandating easy access to human agents will encourage customers to request a human by default, bypassing AI agents,” said Quinlan. “As a result, organizations will have to maintain or even rehire human agents, possibly at higher numbers or at a higher salary than they previously paid. Failure to maintain appropriate staffing levels could lead to deterioration of the customer experience, with customers waiting for long periods to speak to a human.”
Triant said he has already seen that happen among customers.
“You put the technology in, you start running it, and either your users are bypassing it to get to the live agent, or they’re not happy with that, which means you’re not driving better customer experience,” he said. “Your spending goes up, while the problem stays the same.”
One of UJET’s large financial customers had automated 80 percent of its call center work before the AI wave hit, Triant said. They see the next stage of efficiency coming from curating the applications its employees use to fix customer complaints, not reducing the number of people working in the call center.
“The people that are talking to you and I, when we call in for a need, have way too many tools, and it’s so complex,” he said. “‘Oh, hold on. Let me get to that screen. Hold on. That’s trying to load. Hold on, my application is running slow.’ It’s the same story we all know. And when you look at that, the problem is they have so many different things that they have to deal with to get the information they need to solve your problem.”
The sentiment felt by Triant’s customers is helping to fuel the so-called SaaS-pocalypse, which has seen the value of some bellwether software companies fluctuate wildly as investors and the software industry reevaluate the enterprise application stack against the capabilities of artificial intelligence.
Triant said just as UJET isn’t firing its engineers, it is arming them with AI to maximize individual production; its call center customers are looking for ways to do the same thing with their staff.
“How do we take those, the real good knowledge workers and agents, and how do we make them superheroes?” he said. ®