AI Gives Fuel Cards a Smarter Job to Do

Watch more: How AI Is Rewriting How Clients Buy

Artificial intelligence may be entering a period in which the technology itself becomes less important than the way organizations redesign work around it.

That was a central theme during a recent edition of the PYMNTS What’s Next in Payments series featuring Karen Stroup, chief digital officer at WEX. Rather than treating AI as another capability to bolt onto existing software, Stroup argued that companies should reconsider the processes underneath and ask what would happen if they started over.

Her perspective also reframes the familiar discussion of AI as either an aspirin that solves an immediate problem or a vitamin that delivers gradual improvement. While she acknowledged the usefulness of that comparison, she suggested that it captures only a moment in time.

“I really think about this as a holistic treatment plan, not just an aspirin or a vitamin,” Stroup said.

Looking Beyond Individual Features

Many organizations begin artificial intelligence projects by searching for a single pain point to automate. Stroup believes that approach often limits the potential return.

“When you think about the real potential of AI, it’s not about that urgency at the moment of purchase,” she told PYMNTS. “It’s about reimagining how you work and creating a solution that tackles everything.”

That philosophy has influenced the way her teams approach product development. Before introducing artificial intelligence, they first map the existing customer journey, identify unnecessary steps and define what an ideal experience would resemble.

“We encourage our teams to do a service design blueprint,” Stroup said. “Map the experience, talk about what you’re doing today, and then dream big.”

The objective is not simply to speed up an existing process but to determine whether the process itself should exist in its current form.

Measuring Outcomes Instead of Tokens

As enterprises invest heavily in generative AI, many executives monitor adoption through prompt counts or token consumption. Stroup cautioned that those measurements can be misleading.

“If you say, how many tokens do you use, well, you can use a lot of tokens and build a lot of things that don’t matter,” Stroup said.

Instead, she said organizations should evaluate speed of decision-making, product innovation, customer outcomes and operational improvements. Those metrics provide a clearer indication of whether AI is creating business value rather than merely generating activity.

The same philosophy extends to customer products. A feature requires users to remember it exists. A capability embedded within an everyday workflow eventually becomes part of the operating system of the business itself.

Building Around Customer Needs

That thinking shapes the services WEX is developing for its customers.

Within health and benefits, Stroup described a future in which employees no longer scramble to locate receipts weeks after paying with flexible spending or health savings accounts. AI could validate information at the point of care, preserve documentation automatically and eliminate much of the follow-up substantiation process.

The goal is to remove work from the customer rather than create another administrative obligation.

Fuel Cards Become Intelligence Platforms

The same principle appears in fleet management.

Fuel cards generate large volumes of transaction data that can reveal unusual behavior, from out-of-network purchases to repeated fueling patterns that merit review. AI can identify those anomalies quickly and surface them for managers before problems escalate.

Stroup said the system can go beyond producing alerts by drafting communications that help managers coach drivers on appropriate behavior. Rather than simply presenting information, AI supports the next operational step.

That combination of insight and action illustrates how payment products are evolving into decision-support systems instead of transaction tools alone.

The Value of Dreaming Bigger

Stroup also cautioned companies against waiting until artificial intelligence appears fully settled before experimenting.

“AI is inevitable,” she said. Organizations that begin learning now develop experience with data, workflows and governance even when individual experiments fall short of expectations.

For her, the larger risk lies in preserving yesterday’s processes while competitors redesign tomorrow’s.

Watch the full interview with Karen Stroup to learn more about:

Why companies should expect experimentation itself to create organizational value, even when individual AI projects fall short of their original goals.

How embedded intelligence could change year-end benefits planning by helping employees make better funding and enrollment decisions before problems arise.

Why Stroup believes AI will shift managers from performing routine operational tasks toward reviewing recommendations and making higher-level strategic judgments.