Payment Pulse – Ep. 26

Shannon and Michelle discuss why clean payments data, infrastructure ownership, and thoughtful integrations are must-haves before software providers add AI into their product.

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Episode Transcript

 

Shannon: Everyone, welcome back to the Payment Pulse podcast. I’m Shannon.

Michelle: And I’m Michelle. Today we’re diving into a topic that’s top of mind for software leaders everywhere: AI readiness.

Shannon: Just to be clear, AI readiness isn’t about rushing out a chatbot or adding generative AI to your interface. That’s the flashy stuff that everyone notices, but it’s not what actually prepares your platform for the future.

Michelle: Exactly. AI readiness is about the underlying infrastructure, the stuff that determines whether your platform can actually support intelligence later when it’s needed most.

Shannon: Right, so you can’t rely on flashy features if the core systems aren’t solid.

Michelle: And in our world that core is payments, data, and integrations.

Shannon: So let’s start with the big takeaway. AI readiness isn’t about shipping features. It’s about making the right infrastructure decisions today.

Michelle: That’s right. So it might sound a little bit boring at first, but these decisions have a huge impact down the line. If your systems are messy or your data is fragmented now, implementing AI later becomes a lot harder.

Shannon: Exactly. So no AI model in the world can fix inconsistent data or manual reconciliation processes. If your finance team is spending days merging spreadsheets, that’s not smart data. That’s actually a roadblock.

Michelle: It is not just an internal headache either. Fragmented data slows down product development, makes scaling more expensive, and limits your ability to respond quickly to market changes.

Shannon: Clean, consistent payments data isn’t just a nice-to-have. It’s the foundation your platform is built on. So treat it like gold because it literally drives every intelligent decision you’ll make down the line.

Michelle: Now let’s talk about ownership. Not just enabling payments, but actually owning the payments experience and the data.

Shannon: So enabling payments is easy. You plug in a processor, transactions flow, and money moves.

Michelle: But owning it is a real game changer. It means full control over the experience, and more importantly, real-time access to your data.

Shannon: Which is huge. If you wanna do things like dynamic pricing or churn prediction, you can’t make those moves if your data is locked behind a third-party portal.

Michelle: Ownership translates into three major advantages: long-term flexibility, higher platform valuation, and the ability to respond quickly to market or regulatory shifts.

Shannon: Yeah, so think about it. If a competitor introduces a new subscription model or your payment system is messy, slow, or siloed, you’re already behind before you even start.

Michelle: Yeah, and control doesn’t mean micromanaging every transaction. It’s about giving your team the flexibility to innovate without being blocked by infrastructure.

Shannon: So if your payments data is stuck behind CSVs, slow APIs, or a third-party’s roadmap, it’s going to be a real challenge to build anything intelligent on top of it.

Michelle: So speaking of walls, let’s talk about messy integrations. This is the kind of technical debt that sneaks up on you.

Shannon: Yeah, so messy doesn’t mean broken because payments still work. Customers can check out and life goes on, but under the surface it can be chaos.

Michelle: Think one-off integrations, custom middleware, inconsistent onboarding flows, manual reconciliations… it all adds up.

Shannon: And it compounds silently. So if finance has to do manual checks, product teams can’t launch new features quickly. And ops is juggling scripts and alerts.

Michelle: As the costs build up, operational risk grows. Scaling gets more expensive, and your ability to pivot quickly takes a hit.

Shannon: It’s the classic case of it works until it doesn’t, and when a critical initiative stalls or costs spike, it’s painful to unravel.

Michelle: So cleaning up your infrastructure isn’t just a tech project, it’s a leadership and business strategy move.

Shannon: So now let’s talk about the pressure leaders are facing. Everybody seems to be asking, “What’s your AI strategy?”

Michelle: Your board, your customers, competitors- it’s everywhere. And that pressure can make leaders rush AI into critical systems like payments, but that’s a mistake.

Shannon: That’s right because payments touch money, trust, and compliance, and rushing AI here can create reputational risk, regulatory headaches, and stability issues.

Michelle: Imagine an AI pricing algorithm that overcharges customers, or a fraud model that flags legitimate payments by mistake. That’s more than just an operational headache- that directly damages trust.

Shannon: Regulations aren’t impressed by flashy features. So if a model declines a payment, you have to explain why. And not just to the customer, but potentially to auditors too. So there’s no AI shortcut for that.

Michelle: Instead, the smart approach is patience paired with solid groundwork. Standardize your flows, simplify integrations, and choose reliable partners. Build flexibility now so AI can actually deliver later.

Shannon: Exactly, and don’t get caught up chasing the hype. Focus on building a foundation that lets you move confidently when it’s time to bring intelligence into your platform.

Michelle: Okay, Shannon, so let’s get actionable! What can leaders do today to ensure that their software is ready for AI?

Shannon: Sure. So the first thing is to standardize your payment flows. Take a close look at your systems, spot any inconsistencies, and make sure transactions behave the same way across the platform.

Michelle: Great! Step two I would say is to simplify integrations, consolidate providers, remove one-off workarounds, and clean up any extra middleware. The simpler the setup, the easier it is for AI to work across your whole platform.

Shannon: Then step three, I would say, is to pick strong, reliable partners. So things like clear documentation, predictable APIs, and easy access to your data make a huge difference down the line.

Michelle: And remember, this isn’t about rushing AI. It’s about making smart, deliberate choices that compound over months and years.

Shannon: It’s kind of like investing. You can go for the flashy short-term wins, or you can build something that grows steadily over time. And when it comes to AI readiness, the long game wins every time.

Michelle: So here’s the bottom line. AI readiness isn’t about hype. Rather, it comes down to clean data, clear ownership, and thoughtful integrations.

Shannon: Build with flexibility and visibility in mind. Then when it comes time to layer AI into pricing, reconciliation, or customer engagement, your platform will be ready.

Michelle: AI works best when the groundwork is already in place. Without that, it’s just adding complexity.

Shannon: And if there’s one thing to remember, it’s this: prioritize the decisions that make you stronger over time, not just the ones that look impressive in the short term.

Michelle: Exactly, get the infrastructure right first. Then include AI where it truly adds value.

Shannon: So that’s it for today. Thanks so much for tuning in.

Michelle: If you enjoyed listening to this episode, we have more resources like this on our blog at xplorpay.com. That’s X-P-L-O-R pay.com.

Shannon: Thanks so much for listening today, and we’ll see you next time on Payment Pulse.