Brad Anderson, the president of product, user experience, and engineering at Qualtrics, an $11 billion company that helps businesses collect and analyze data, believes organizations are at a turning point in how they apply AI.
“AI is no longer just in the back office,” he told Business Insider. “It’s front and center in every customer and employee conversation, and it’s being brought to organizations in ways they can tangibly see and benefit from.”
At the heart of this shift is agentic AI, he said. While generative artificial intelligence helps companies interpret data to better understand customer behaviors and trends, agentic AI goes a step further by “unlocking action at scale,” Anderson said. This allows businesses to respond to those insights quickly and effectively.
Last year, for example, Qualtrics, which made its name in customer surveys, introduced conversational feedback, using AI to analyze responses and generate real-time follow-up questions. Today, the company works with over 20,000 customers across industries — including tech, retail, and airlines — and is using agentic AI to help them turn feedback into actionable insights and respond more effectively.
Some organizations are leading the way, while others are more cautious. “Some are carefully evaluating how it benefits their customers and employees,” Anderson said, “while others see it as transformative not just for their business but for the world — and they’re eager to get after it.”
BI spoke with Anderson about how companies could use agentic AI.
The following has been edited for clarity and length.
You say that agentic AI drives “action at scale.” Can you give an example?
Imagine an airline passenger’s flight is canceled and they’re unsure about the refund process. When they respond to a survey, they might say, “I searched online but still don’t know if I’ll get my money back or just a credit.”
With agentic AI, we personalize responses in the airline’s tone and act based on the customer and their situation. Instead of a generic reply, the system confirms refund eligibility, gives a timeline, and tailors responses based on loyalty status and lifetime value. A highly profitable, loyal customer gets a different experience than someone who booked through a discount site. This turns a routine survey into a real-time service, resolving issues instantly.
Beyond surveys, where else is agentic AI making an impact?
Say a customer is on a retail site trying to buy sneakers, but the system won’t let them enter their credit card’s CVV in checkout. We’ve all been there. Our AI detects signals of digital frustration in real time — things like mouse thrashing, rage clicking, dead links — and triggers a pop-up AI agent: “Hey, looks like you’re having trouble checking out. How can we help?”
The customer says, “I’m trying to enter my CVV, but it’s not working.” The agent responds, “We’re sorry about that. Let’s see if we can fix it.” If the issue can’t be resolved immediately, it suggests an alternative payment method, like PayPal or Apple Pay. At the same time, in the background, our system flags the issue to the digital team, helping to fix the underlying problem for future customers.
How do you see agentic AI changing the way customers shop online?
By giving relevant recommendations. Say a customer visits a sporting goods site looking for a sonar for fishing. The agent recognizes their past purchases and says, “Looks like you fish freshwater in the Ozarks. Is that right?” When the customer confirms, the AI, trained on the company’s data, recommends five models. The customer can ask, “What’s the difference?” or “Which one does X?” Once they decide, the agent adds it to their cart. Think of it like a digital concierge.
To be clear, these are all different agents, right? And how should companies approach this?
We’re going to operate in a multiagent world. There won’t be one agent used everywhere. Agents will interact both across and within organizations and integrate into existing research programs, brand trackers, and employee experience workflows.
To take full advantage of agentic AI, companies need to expand where they’re gathering customer feedback and be truly omnichannel. If they’re only doing surveys and ignoring reviews and social media, they’re missing out.
One of our customers processes over 100 million reviews annually from their own and competitors’ locations. Many large brands use ticketing workflows and templated responses, but our AI scans reviews and suggests personalized, on-brand replies focused on the specific experience. This lets them respond at scale, as soon as reviews are posted, across more than 15 websites. The key is closing the loop as part of the listening system.
