Insights from AltoPay, Payzli, and Maverick Payments

AI is rapidly reshaping how payments companies build products, support merchants, and scale operations. But in a regulated industry where mistakes carry real financial consequences, the question is not simply how to adopt AI. The question is where it actually improves outcomes and where human judgment still matters most.

That was the focus of Coris’ recent webinar, Where AI Belongs (and Where It Doesn’t) in Payments, moderated by Ken Musante and featuring leaders from across the payments ecosystem:

• Joe Emig, Chief Revenue Officer at AltoPay
• Kapil Pershad, Co-founder and CPTO at Payzli
• Ben Griefer, President and COO at Maverick Payments

Across operations, engineering, and commercial teams, the discussion revealed several practical ways payments companies are already applying AI today—along with clear boundaries for where automation should stop.

Watch the full webinar here.

The conversation surfaced four key insights for payments leaders evaluating how AI fits into their organizations.

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AI is delivering early wins in operational workflows

Many of the most immediate gains from AI are appearing in high-volume operational workflows.

Ben Griefer described how Maverick Payments is applying AI across processes such as merchant onboarding, underwriting support, ticket routing, reconciliation assistance, and chargeback guidance. These workflows often involve gathering information, validating documentation, and routing requests to the appropriate team.

As payment platforms grow, these tasks can quickly become operational bottlenecks.

AI helps automate much of that groundwork so teams can focus on the work that requires experience and judgment. Routine operational tasks can be handled faster and more consistently, allowing human teams to concentrate on exceptions and complex cases.

Merchant support illustrates this well. Small business owners often handle administrative tasks after hours. AI can provide immediate answers for straightforward questions while escalating more complicated issues to human support teams.

The result is smoother merchant experiences and operations that can scale without the same level of administrative overhead.

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AI is accelerating how payments software gets built

Engineering teams are seeing a different type of impact.

Kapil Pershad explained how Payzli has begun incorporating AI across its software development lifecycle. Roughly a quarter of the company’s codebase already involves AI-assisted development.

AI tools are helping teams:

• Write code
• Generate test scripts
• Review code for potential issues
• Document systems
• Refactor legacy code

Tasks that once took weeks can now often be completed in days.

At the same time, Pershad emphasized that trust in these tools still depends on human oversight. Developers review outputs and validate results, particularly in a regulated industry like payments where reliability and security are critical.

AI can handle much of the granular work, but humans remain responsible for the final decisions.

That balance allows engineering teams to move faster while maintaining the standards required for financial infrastructure.

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AI is strengthening research and preparation in sales

AI is also changing how commercial teams prepare for merchant conversations.

Joe Emig described AI as a “ride-along consultant” for sales teams. With the right prompts, AI can help analyze merchant prospects, identify potential pain points, and better understand competitive positioning.

This allows sales teams to enter conversations with a deeper understanding of a merchant’s business and industry.

However, Emig cautioned against over-reliance on AI when communicating with customers.

He shared an example of a follow-up email after a business call that was clearly written by AI. The structure and tone made it obvious, and the message felt impersonal.

In a relationship-driven industry like payments, that kind of interaction can quickly undermine trust.

AI can accelerate research and help draft materials, but sales teams still need to personalize communication and maintain their own voice.

Relationships remain central to how payments companies win and retain business.

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Human judgment remains critical in high-risk decisions

Despite the productivity gains AI can deliver, the panelists were clear that automation should not replace human oversight in high-risk scenarios.

Payments companies operate in a highly regulated environment where even small errors can create meaningful consequences.

Ben Griefer noted that a model that is wrong even a small percentage of the time can still create significant exposure when applied to merchant underwriting or risk monitoring.

AI can gather signals, organize information, and surface recommendations. But final decisions in sensitive areas still require human judgment.

The strongest implementations combine automation with oversight. AI handles the routine work while experienced operators evaluate complex or ambiguous cases.

As Ken Musante summarized during the discussion:

“AI should increase clarity, not replace responsibility in payments.”

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AI is increasingly embedded across payments tools

The discussion also highlighted how quickly AI capabilities are evolving.

Kapil Pershad noted that tasks AI struggled with only a few months ago are already improving as models integrate with development tools, threat databases, and new data sources. That pace of change means payments companies must continually reassess where AI adds real value.

Joe Emig offered a useful analogy. Years ago the industry spoke about “mobile commerce” as a distinct concept. Today it is simply part of how commerce works.

AI may follow a similar path.

Rather than existing as a standalone category, AI is increasingly embedded into the platforms and tools payments companies already rely on.

For operators across the payments ecosystem, the challenge is not becoming AI experts. The real challenge is understanding where AI improves speed and insight while preserving the human judgment that payments infrastructure ultimately depends on.

Payments leaders who strike that balance will be best positioned to capture the benefits of AI without compromising the control, trust, and accountability that define the industry.