Qualtrics CEO Jason Maynard on the Future of Experience Management

For years, experience management has been built around a relatively simple model: listen, understand, act. Companies collect feedback. They measure satisfaction. They map customer journeys. They identify problems and then try to fix them. But AI is changing what comes next.

I recently sat down with Jason Maynard, CEO of Qualtrics, to talk about the future of experience management and how AI is changing the way organizations understand, predict, and deliver experiences. The biggest shift may be moving from looking backward to predicting the future.

From the rearview mirror to simulation

Maynard describes the evolution of experience management as a move from understanding what happened to predicting what could happen next.

His analogy is Formula 1 racing. Teams don't simply look at what happened in the last race. They use massive amounts of data and simulation to test strategies and anticipate different outcomes before race day.

Maynard believes organizations will increasingly do the same with their customer and employee experiences. Companies could simulate changes to pricing, product packaging, customer engagement, employee interactions, and other experience outcomes before making those changes in the real world.

That could make testing both cheaper and more precise. Instead of waiting for an experience to happen and then measuring the result, companies can increasingly ask:

What happens if we change this? And then test it before making the decision.

The journey map is becoming an experience loop

One of the more interesting ideas from the conversation is the shift from journey maps to experience loops.

Journey maps are static. They describe a path through an experience and often require people to manually determine what happens next. Experience loops are different. They are continuous. They can adapt based on new information, simulate different paths, and keep learning from what happens.

That matters because customers don't experience companies in neat, linear journeys. They move between channels, products, people, and systems. Their needs change. Their behavior changes. Their context changes. AI makes it possible to adapt continuously to those changes rather than relying on a journey map that eventually ends up sitting in a drawer.

Experience may be the differentiator AI can't easily copy

We also talked about why experience is becoming even more important. Products can be copied. Pricing can be copied. Technology can be replicated.

Experience is harder. The challenge is making that experience personal at scale. A customer doesn't want an organization to simply know their data. They want it to remember their preferences, understand their context, and respond accordingly.

That requires more than another application. It requires organizations to connect the data and signals that already exist across the enterprise.

AI doesn't eliminate the data problem

There is an obvious catch. Simulation is only as good as the data behind it.

Maynard argues that Qualtrics' advantage comes from more than two decades of experience data and its ability to organize that information through an experience ontology. The bigger enterprise challenge is connecting that experience intelligence with the rest of the organization's data.

Most companies have already accumulated massive application and data sprawl. SaaS multiplied the number of point products, and each one created another source of information. AI can reason across those systems, but organizations still need to know which data matters, what it means, and where the gaps are.

The problem isn't simply having more data. It's having the right context.

Decision velocity becomes the new advantage

Perhaps the biggest implication is organizational. AI isn't just changing the technology stack. It's changing how quickly companies can make decisions. If organizations can simulate more options, learn from more signals, and continuously close the loop between action and outcome, the distance between strategy and execution starts to shrink.

That is what Maynard calls decision velocity. And it could become one of the most important measures of AI maturity. The winners won't necessarily be the companies with the most AI. They'll be the companies that can use AI to learn faster, decide faster, and adapt faster.

The next era of experience management isn't just about listening. It's about simulating, predicting, and continuously delivering better experiences continuously.