LAS VEGAS — AI and its many use cases are hot topics for contact center leaders, and as they navigate the ever-growing sea of vendors and solutions, they need to cut through the hype to find the applications that fit their needs.
A panel of CX leaders from companies including Walmart and Fanatics discussed their experiences with AI at the end of the first full day of Customer Contact Week Las Vegas. Their discussion busted some of the myths around the technology and shared lessons from their successes.
Several key themes emerged. Leaders discussed the importance of using AI to enhance specific strategies rather than cover up problems, ensuring that transparency goes beyond offering customers an incomprehensible list of legal terms, and looking beyond customer-facing chatbots to use the technology to its full potential.
If contact center teams can look beyond AI as a buzzword and use it to find breaks in their systems and solve customer problems, they can make it so customers never have to call them again, according to Anderson Wilkins, director of product management, agentic self-service and AI defect detection at Walmart.
AI is a tool — not a solution
Few doubt that AI is in the process of revolutionizing customer service, but there is a tendency to overplay its potential. It’s powerful and versatile, but it doesn’t solve problems by itself.
AI is just one tool in the toolbox, according to Bob Sacunas, VP and strategic industry executive at UiPath. Leaders need to know why they’re using it before moving forward with an investment.
“You could drive in a nail with a wrench in a pinch, but why would you do that if you have a hammer?” Sacunas said on the panel. “And yet, I see a lot of organizations doing the same thing with AI. We're under pressure to do more with AI, and we start throwing it at things where it's really not the best solution.”
Instead, leaders should take a step back and consider the implications of different AI use cases.
One of the most common misconceptions is that AI can unify fragmented customer support processes, according to Wilkins. However, AI doesn’t fix problems, it builds on an existing foundation.
“If your policies are inconsistent, your data is incomplete, if your channels give different answers — AI is not going to magically fix that,” Wilkins said. “AI is a multiplier. It's going to multiply really great experiences, and it unfortunately can multiply some really poor experiences for your customers and members.”
Transparency is about more than words
Customers value transparency in customer service, especially around AI, but letting customers know they’re talking to a bot is just the first step.
Transparency needs to be understandable, according to Wilkins. Disclosures can often devolve into paragraphs of legal jargon, and it’s better to present information in a way that lets customers know what the company is doing with AI or their data and why it’s happening.
Disclosure is just the start of transparency in customer service, according to Megan Merrick, director of collector experience at Fanatics. Customers want to know when they’re talking to a bot, but that won’t make or break a relationship. What they care about is whether that bot is actually helping them.
“Is that experience working well?” Merrick said. “Then yes, you're going to build trust with your customer base, they're going to feel better about reaching out to you. But if it doesn't work, you're losing customer trust to a higher degree.”
As a result, Merrick designs AI customer service with the failure state in mind, focusing on mitigating the worst case scenario rather than immediately focusing on the maximum potential. Failures are more common than successes after launch, and minimizing frustration with AI can prevent customers from writing it off entirely.
Customer-facing AI agents aren’t always the best use case
AI agents are the most visible application of the technology in customer service, but they aren’t the only one, or even the right option for every company.
The best AI strategy reduces the effort customers need to spend to solve their problems, according to Wilkins.
“I think the full goal of this is utilizing AI to understand what are those contact drivers, what are those intents, what is the friction behind those repeat calls,” Wilkins said. “To be able to synthesize the data and be able to point to that information, that intelligence, at exactly the right processes and products that actually need to be changed.”
The big question is whether you focus your AI investments on the needs of the customer or the needs of the workers, according to Brent Nelson, VP of the virtual communication center and virtual experience at Wellby Financial, a Texas-based credit union.
Assisting customers is the straightforward option, but using AI to support the customer service team behind the scenes trickles down to assisting consumers as well, according to Nelson. Teams need to look for the less obvious benefits employee-facing AI can offer before making their decision.
“We went from zero to 100 trying to appease our membership, when in reality we should have started with our team members, because then we would have seen a much better result and a much quicker return on our investment,” Nelson said.
