LAS VEGAS — Artificial intelligence and its many use cases have become a hot topic among contact center leaders. Faced with a growing market of vendors and solutions, decision-makers need to cut through the hype to find use cases that truly fit their needs.

At the end of the first full conference day of Customer Contact Week in Las Vegas, a roundtable discussion featuring customer experience (CX) leaders from companies like Walmart and Fanatics shared their firsthand experiences with AI, debunking some myths about the technology while also summarizing lessons learned from successful implementations.

Several key themes emerged from the discussion: leaders emphasized using AI to strengthen specific strategies rather than mask systemic flaws; ensuring transparency goes beyond showing customers a list of obscure legal terms; and expanding the vision beyond customer-facing chatbots to fully tap into the technology's potential.

Anderson Wilkins, Director of Product Management for Agent Self-Service and AI Defect Detection at Walmart, noted that if contact center teams can move beyond treating AI as a buzzword and instead use it to identify breakpoints in their systems and resolve customer issues, they can ultimately make it so customers no longer need to call for help.

AI is a tool, not a cure-all

Few doubt that AI is reshaping the customer service industry, but its capabilities are often overestimated. AI is powerful and versatile, but it cannot solve problems on its own.

Bob Sacunas, Vice President and Head of Strategic Industries at UiPath, believes AI is just one tool in the toolbox. Leaders must clarify their purpose for using it before advancing investments.

"In an emergency, you can use a wrench to hammer a nail, but why bother when you have a hammer?" Sacunas said during the panel. "However, I see many organizations doing exactly that with AI. We feel pressure to do more with AI, so we start applying it to areas where it isn't actually the best solution."

Instead, leaders should step back and carefully consider the potential impact of different AI use cases.

Wilkins pointed out that one of the most common misconceptions is that AI can unify fragmented customer support processes. However, AI cannot fix problems; it can only build on what already exists.

"If your policies are inconsistent, your data is incomplete, and different channels give contradictory answers—AI won't magically solve those problems," Wilkins said. "AI is a multiplier. It can amplify great experiences, but unfortunately, it can also amplify poor experiences for customers and members."

Transparency goes beyond disclosure

Customers value transparency in customer service,especially when it comes to AI,but letting customers know they are talking to a bot is just the first step.

Wilkins believes transparency must be easy to understand. Disclosure statements often devolve into lengthy legal jargon; a better approach is to inform customers, in a way they can understand, how the company uses AI or their data and why.

Megan Merrick, Director of Customer Experience at Fanatics, said disclosure is just the starting point for transparency in customer service. Customers want to know if they are interacting with a bot, but that doesn't make or break the relationship. What they really care about is whether the bot is actually helping them.

"Is the experience smooth?" Merrick asked. "If it is, then you can build trust with your customer base, and they'll be more willing to reach out. But if the experience is poor, you lose even more customer trust."

Therefore, when designing AI customer service, Merrick prioritizes failure scenarios, focusing on mitigating the impact of worst-case situations rather than initially aiming for maximum potential. After deployment, failures are often more common than successes, and minimizing AI-induced frustration can prevent customers from abandoning it altogether.

Customer-facing AI agents are not the only best use case

AI agents are the most visible application of the technology in customer service, but they are not the only option, nor are they necessarily the right fit for every business.

Wilkins believes the best AI strategy is to reduce the effort customers expend to resolve issues.

"I think the ultimate goal of all this is to use AI to understand what the contact drivers are, what the intents are, and what the friction points are behind repeat calls," Wilkins said. "Then we can consolidate data and point that information and intelligence precisely at the business processes and products that truly need to change."

Brent Nelson, Vice President of Virtual Contact Center and Virtual Experience at Wellby Financial, a Texas-based credit union, raised the key question: Is your AI investment focused on customer needs or employee needs?

Nelson noted that directly assisting customers is the obvious choice, but using AI behind the scenes to support the customer service team ultimately benefits consumers as well. Teams need to uncover the less obviousbenefits。

"We went from zero to a hundred, eager to delight members, but actually we should have started with our team members," Nelson said. "If we had, we would have seen better results, and the return on investment would have come faster."