Green Sheet interviews John Cimba, CEO of Stax Payments

Artificial intelligence promises to help small businesses operate more efficiently, but determining where the technology can deliver meaningful value, and where human judgment should remain firmly in the loop, is still a work in progress.

In this Q&A John Cimba, CEO of Stax Payments, checks in with The Green Sheet about practical AI applications in payments, from merchant onboarding and administrative tasks to the role ISOs and payments providers can play in helping merchants evaluate and adopt AI responsibly.

Green Sheet: Where can AI create the most meaningful value for small merchants today beyond simply reducing labor or costs?

John Cimba: For small businesses, I think the bigger opportunity is looking at AI as a way to create time capacity. When you run a small business, time is one of your most valuable resources. If AI can take repetitive or administrative work off your plate, the question becomes: what can you do with those hours that actually moves the business forward? 

In our research, we asked merchants what they would do if AI saved five hours a week, and 38 percent said they would put that time toward revenue-generating activities, while 35 percent said they would invest it in strengthening customer relationships. That shows that small businesses are looking at how AI can free up time rather than replace someone or something. 

If a business owner can spend less time on administrative tasks and more time talking to customers, finding the next customer, developing a new offering or supporting employees, the value becomes much bigger than cost savings. 

GS: What payment-related administrative tasks are especially well suited to AI, and why?

JC: I would first look at processes that are repetitive, manual and take merchants away from actually running their businesses. For example, with onboarding, there can be a lot that happens between closing a new merchant and getting that merchant to the point where they're able to accept payments.

If AI can streamline parts of that process, identify missing information or reduce unnecessary back-and-forth, then that's meaningful. That frees up time elsewhere for more meaningful work. This is especially valuable for SMBs, where owners and employees often wear multiple hats and may not have dedicated teams to manage payments administration.

There are opportunities across other administrative areas as well, but I don't think the goal should be to put AI everywhere just because we can; instead, we have to start with the pain point. That being, where is a merchant or their provider spending time on something that technology would handle faster or more efficiently? 

The standard that I continue to come back to is whether we're making the experience faster and better for the customer—meaning our engagement with our merchants and the merchants with their customers as well. If AI can reduce the amount of time a small-business owner spends dealing with payments administration and get them back to running their business, that's a practical use of the technology. 

GS: You point to "invisible" AI working behind the scenes. What might that look like in a merchant's day-to-day operations?

JC: The best AI for a small-business owner may be AI they barely have to think about. They shouldn't have to learn a new tool or become an AI expert to benefit from it. When thinking about all of the things happening behind the scenes of a business, such as invoicing, organizing information, identifying when something needs attention, answering routine questions, generating reports, sending automated alerts, or helping resolve an issue faster, there are opportunities for AI to be used to simplify the process. 

From a merchant's perspective, the result might just be that something that used to take hours takes minutes, they get an answer faster, or there's less paperwork standing between them and accepting a payment. We've seen companies like Uber and Starbucks succeed by making payments and loyalty feel seamless and frictionless for the customer.

AI can help bring that same level of simplicity to more businesses by handling complexity behind the scenes. That's what I mean by making AI invisible. The merchant experiences the outcome rather than the technology. 

GS: How can AI streamline merchant onboarding and shorten time to payment without introducing new fraud or compliance risks?

JC: Payment companies have to be thoughtful because speed matters to small businesses, but you can't create speed by removing the controls that protect the merchant and the payments ecosystem. 

I see AI as a tool for making the process around the controls more efficient. It can potentially help organize information, surface missing information earlier and identify where something may require additional review. That can allow people to spend more of their time on the cases that actually require human judgment instead of treating every application as equally manual. 

The goal is to compress the time between starting to accept payments and being able to actually accept the payments, while maintaining the appropriate risk and compliance standards. For a small business, getting to that point faster isn't just a better payment experience; it can mean getting to revenue faster. 

GS: What role should ISOs and payment providers play in helping small merchants adopt AI tools they may not have the expertise to evaluate themselves?

JC: We shouldn't expect every small business owner to suddenly become an AI expert because they have a business to run and focus on. That's where the provider has a responsibility to understand the technology, determine where it can create real value and build it into the experience in a responsible way. 

Putting AI into a product isn't automatically innovation; there has to be an architecture behind it, and importantly, there has to be a person who understands what you're trying to accomplish with it. 

For ISOs and payments providers, I think the opportunity is to help remove that burden from the merchant. Evaluate where AI makes sense, put the right security and compliance guardrails around it, and use it to solve actual business problems.

That opportunity may also extend beyond payments. Providers, ISOs and VARs should be exploring trusted third-party AI tools that can support adjacent areas of the business, such as marketing and content, where our research shows SMBs are already more comfortable using AI.

They can help merchants assess which tools are credible, secure and genuinely useful rather than expecting them to navigate a crowded market alone. The merchant shouldn't have to understand the model underneath the hood. They should be able to see that the service is faster, easier or more useful to their business. 

GS: How can merchants find the right balance between AI automation and human judgment? Is that likely to require trial and error, or can payments providers help them establish the right boundaries from the outset?

JC: It will take some time for merchants to learn as the tools evolve, but I don't think that businesses need to start from zero. One useful principle is to look at both the task and the consequences of getting it wrong.

AI can be very effective at helping with repetitive work, organizing information, identifying patterns and making processes more efficient. But as the stakes of a decision increase, human judgment becomes more important. That is particularly true in areas involving money, risk, compliance or important customer relationships. 

Our research suggests merchants are already thinking along those lines. They are more cautious about using AI for financial, legal or insurance guidance, where an inaccurate answer can carry much greater consequences. Their concerns about expanding AI use also include data privacy and security, accuracy, and regulatory or legal risk. Those are the areas where clear boundaries and human oversight become especially important.

Payments providers can help establish those boundaries because they understand both the technology and the regulatory environment merchants operate within. To me, the right model isn't human versus AI. It's figuring out what technology can take off someone's plate while keeping people involved where their experience, context and judgment matter most. 

AI still needs a brain telling it what to do. The companies that get the most value from it won't necessarily be the ones that automate the most. They will be the ones that are clearest about what they want AI to accomplish and then use the time it gives back to create more value for their customers and business.

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