Payments leaders would be forgiven for equating the word “legacy” with old rails, monolithic systems and slow-moving infrastructure.
In the age of artificial intelligence, the instinct across financial services has been to modernize aggressively, automate relentlessly and replace anything that appears too slow, too rigid or too institutional to keep pace with software-native competitors.
But Dean M. Leavitt, founder and CEO of Boost Payment Solutions, told PYMNTS during a discussion for the May edition of the “What’s Next in Payments” series, “When Legacy Becomes Leverage,” that the true competitive fault line is now organizational mindset.
“When people think of legacy, the first thing they think of is infrastructure,” Leavitt said. “I would argue that a big piece of the changes that are going on with legacy right now actually relate to mindset.”
That changing mindset is what now determines whether institutions can adapt fast enough to incorporate AI, data intelligence and evolving customer expectations without destabilizing the trust, compliance and credit structures that underpin global commerce.
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“Legacy” infrastructure becomes less a liability than a distribution layer waiting to be reprogrammed, Leavitt said.
The Payments Stack Is Becoming Layered and Not Replaced
The companies gaining traction across payments are often not the ones replacing the old stack wholesale, but those learning how to layer intelligence, automation and new workflows onto systems that still perform critical economic functions well. In commercial payments, few examples are clearer than credit.
“In payments and specifically in card-based payments, credit extension is the one thing that is in many cases paramount to both buyers and suppliers,” Leavitt said.
Commercial card infrastructure continues to solve a uniquely difficult balancing act in enterprise finance, he said. Buyers gain working capital flexibility and extended days payable outstanding (DPO), while suppliers can accelerate receivables and reduce days sales outstanding (DSO). That dual benefit has preserved the relevance of card networks and credit rails despite the proliferation of real-time payments, stablecoins, embedded finance platforms and AI-native FinTech tooling.
“It’s just the magic of the credit card processing industry that we’ve seen for 80 years,” Leavitt said. “There’s this whole layer, primarily financial technology companies, that have operated on top of that as a separate layer to answer the needs of the customer.”
While FinTech discourse often frames innovation as displacement, enterprise payments remain dependent on trusted financial rails that already solve liquidity, risk and settlement challenges at a global scale.
What changes instead is the layer above those rails. At the base are the original processors, issuers and regulated financial institutions that established the infrastructure underpinning modern commerce. Above them sits an increasingly sophisticated FinTech layer designed to make those rails more flexible, data-rich and enterprise-friendly.
“You can also look to companies, frankly, like Boost,” Leavitt said. “We’ve bent those rails in ways through our technology, our processes, our procedures.”
That bending increasingly revolves around data orchestration. Enterprise buyers and suppliers require more contextual information than traditional payment rails were originally designed to exchange. The competitive opportunity for FinTech firms lies in improving how transactional data moves between counterparties and integrating payments into procurement, accounts payable and treasury workflows.
AI does not erase incumbency advantages if incumbents own unique data. It may actually amplify them.
AI’s Real Competitive Advantage in B2B
If legacy infrastructure still matters, AI is reshaping how companies extract value from it. For Boost, that means nearly two decades of enterprise payment activity spanning billions of dollars in transaction volume. The strategic value lies not simply in possessing that data, but in using AI to identify procurement patterns, supplier behaviors and emerging operational trends faster than rivals.
“We’re using AI as that tool against our proprietary data really as a weapon vis-à-vis competitors,” Leavitt said.
Still, he was careful not to frame AI as autonomous decision-making infrastructure, particularly in payments, where precision is non-negotiable. Instead, Boost has introduced layered oversight systems, including AI agents monitoring the work of other AI agents alongside human supervision. The approach reflects a more measured implementation philosophy than the “move fast and automate everything” posture common across parts of the tech sector.
“AI is certainly transformative,” Leavitt said. “But it needs to be properly embedded into the right solution, into the right process, and carefully monitored.”
“You cannot just blindly trust it,” he added. “We don’t deal with rounding errors.”
Consumerized Expectations for Enterprise Payments
Historically, enterprise software and payments tolerated friction because switching costs were high and buyers were institutional. But that tolerance is disappearing as the next generation of digitally native finance decision-makers climbs the corporate ladder.
“They grew up buying things online and don’t see why they should have a significantly different experience across procurement or AP spend for their company,” Leavitt said.
That expectation gap is forcing traditional financial institutions to rethink not only interfaces and workflows, but partnerships.
“Many of the financial institutions, the larger behemoths, have really, over the last several years, come to the conclusion that they can’t build out most of the enhancements quick enough,” Leavitt said. “Companies like ours that are very agile, that have our ears constantly to the ground in the marketplace and know what the market needs, and maybe what the market needs next year or the year after. It’s working quite well.”
In that sense, legacy itself may no longer be the liability. The real risk is treating legacy as static.
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