How we approached AI in banking customer experience and what worked

In this special guest post, Rob McGregor from Emprise Bank shares how connected, AI-enabled experiences are reducing effort and improving customer relationships.

Customer experience transformation in banking doesn’t happen through a single, big technology decision. It happens through small, intentional changes that reduce effort, build confidence, and strengthen relationships. Taking this into account has guided how we’ve approached AI, not as a standalone initiative, but as a practical way to improve how customers experience our bank every day.

I’ve learned that AI in banking customer experience only added value when it was tied directly to what customers were experiencing. We didn’t bring it in to check a box or show progress. We brought it in because customer behavior and feedback pointed to very specific friction points we needed to address. Over time, it became clear that the real impact of AI had less to do with the tools we chose and more to do with how intentionally we integrated them into the experience.

Start with the customer problem.

One of the easiest mistakes to make with AI is starting with the technology instead of the experience. Like most banks, we had access to powerful tools. The real work was deciding where to apply them. Instead of leading with AI, we focused on the parts of the experience that weren’t working as well as they should. Instead of asking What can AI do? We asked, Where are customers getting stuck?

If AI couldn’t make an experience clearer, faster, or more intuitive, we didn’t pursue it. And if it introduced even a hint of risk to trust or safety, it was a non-starter. We tested every deployment thoroughly and continued to monitor it after launch to ensure it stayed accurate, transparent, and helpful.

Keeping the customer at the center of every decision helped us innovate while staying aligned with our risk culture. In my experience, banking CX transformation only succeeds when innovation and discipline go hand in hand. One without the other eventually breaks.

Breaking the silo mindset in banking CX.

One assumption we intentionally challenged was the idea that each channel should operate independently. Traditionally, banking experiences are fragmented: IVR systems behave one way, digital banking another, and after-hours support often feels like a completely different institution. Customers feel that disconnect immediately, even if we don’t.

We deliberately shifted toward connected experiences. We needed our systems to work together and share context so the experience made sense for the customer. That’s what enables improvements like IVR follow-ups via text, more relevant prompts in digital banking, and after-hours AI support that feels consistent with what customers get during the day.

Instead of feeling like a series of disconnected interactions, the experience began to feel whole. Customers no longer had to start over, depending on where or when they reached out. That reduction in effort is foundational to the banking customer experience transformation, and customers notice it long before they articulate it.

Using AI to strengthen, not replace, human connection.

One of the most impactful shifts we made was directing AI insights to our frontline teams. AI is usually framed as something that replaces people, but we saw it as something that could support them.

Real-time insights allow associates to understand what a customer might be feeling in the moment. If someone is frustrated, the system can surface coaching prompts or suggested empathy statements—not scripts, but guidance that helps associates respond thoughtfully. Predictive insights highlight what matters most to a customer right now, so conversations stay focused and relevant.

This type of support also reduces missteps, builds confidence, and allows our bankers to spend less time searching for information and more time connecting with the person in front of them. In practice, this is where AI banking customer experience becomes real, not through automation alone, but through better human interactions enabled by it.

Designing AI experiences that customers want to use.

AI can’t live only behind the scenes. Customers expect support on their terms, especially outside traditional banking hours. That’s why we leaned into customer-facing AI across chat, text, and digital banking, fully integrated with our core systems. The integration is critical. Without it, AI feels shallow and transactional; with it, customers can self-serve in intuitive, consistent ways, whether they’re across town or across the world. Even without an international phone plan, they can access guidance, resolve issues, or receive personalized recommendations.

AI quickly became a trusted part of the customer experience. Our AI assistant didn’t create distance; it created availability. And paired with empowered associates during business hours, it ensured the experience traveled with the customer. That continuity has been a major driver in our customer experience transformation in banking, especially when customers move beyond our physical footprint.

Where we took a risk and what we learned.

Fully embracing AI agents in banking is not without risk. If the experience feels clumsy or dismissive, customers will quickly abandon it. We were very aware of that going in. The potential downside included higher escalations, lower satisfaction scores, missed opportunities, and erosion of trust.

What happened was the opposite. Customers continued using AI, began personifying it, and even thanked it as they would a human agent. That wasn’t something we engineered; it was earned by making the experience useful, responsive, and respectful of the customer’s time. The bot now handles routine questions efficiently, which frees our bankers to focus on complex, high-value conversations. That balance reinforced something we believed early on: when AI reduces friction instead of deflecting responsibility, it can strengthen loyalty rather than create risk. For us, that was a defining moment in our banking CX transformation.

Measuring what matters.

Without clear measurement, it’s impossible to know whether the experience is improving or just changing. Standard CX metrics still matter, but they need to be paired with a deeper view of the customer journey. We started paying closer attention to customer effort—how easy it is for someone to get what they need, regardless of channel. AI should lower effort, not just speed things up. We also closely examine AI-assisted first-contact resolution. Resolution alone isn’t enough. Customers need to feel understood and supported, and associates need the right insights to respond confidently. Measuring both sides of that interaction gives us a more complete picture.

Equally important, we measure AI interactions the same way we measure human ones. Customers who engage with our AI experiences receive the same surveys. That consistency keeps us honest and ensures the experience remains aligned with our standards.

What I wish more leaders understood about AI.

If there’s one thing I’d emphasize, it’s that AI is not a technology project—it’s a people and experience strategy. The real value doesn’t come from chasing efficiency metrics but from reducing friction, building confidence, and amplifying human connection.

What’s consistent throughout this change is the importance of trust. When customers feel understood and supported, whether through AI or a human interaction, they continue to engage. That sense of continuity has shaped how we think about customer experience and has been the most meaningful outcome for us.