Artificial intelligence is reshaping every industry, but for financial institutions, the opportunity extends far beyond automation. As customer expectations evolve, conversational AI is creating new ways to deliver more personalized, proactive banking experiences while strengthening the relationships that have always set community institutions apart. 

Daniel Haisley, Chief Data & AI Officer at CSI, helps shape the company’s AI strategy while working with financial institutions to turn emerging technologies into practical solutions that enhance the customer experience.  

We sat down with Daniel to discuss conversational AI, data strategy, responsible AI, and why community banks may be better positioned than they realize. 

What excites you most about the opportunity AI creates for community financial institutions?

“Community financial institutions generally fall into a couple of categories. There is a small number that is willing to be on the leading edge, and then there is a much larger group that says they want to be fast followers. 

The reality is that everyone can’t be a fast follower. The institutions that are successful lean into what makes them different. They focus on relationships. They know exactly who they serve best. Otherwise, they’re competing on locations and rates, and that world is going away. 

What’s exciting about AI is that it’s one of the first technologies that really gives community banks the opportunity to punch above their weight class. They can compete with anyone if they use it thoughtfully and deploy it at scale.” 

A lot of people still hear “conversational AI” and think “chatbot.” What are they missing?

“Chatbots to date have been crude relative to what they’re about to be. It’s like if someone says “television” and they’re envisioning a 1980s 24” console TV while we’re barreling into the world of 80” OLEDs. Chatbots armed with conversational AI capabilities are vastly more powerful (and useful!) than their predecessors.” 

What do financial institution leaders misunderstand about conversational AI, and what should they be preparing for now?

“Conversational AI isn’t a defined industry phrase yet. Thus, it doesn’t carry the type of context that would lead bankers one way or the other beyond the descriptive name itself.  

On that front, the biggest opportunity for misunderstanding is the belief that “conversational” means the user is engaging in an audible conversation – which is not the case.  

Instead, conversational AI refers to the ability to communicate in written or audible form, with an AI agent, using natural language. For customers of a bank, conversational banking means that you’re able to engage with your finances as though you were communicating with a financial advisor.” 

What does a truly useful conversational banking experience look like in digital banking?

“The ideal conversational banking experience begins with the bank proactively reaching out to the customer saying, “It looks like you have a bill which needs paid, would you like me to pay that for you?” to which a simple “yes” completes the task.  

The experience is curated for that person based on their exact needs at that moment. It didn’t require them to kick off the process but instead provided proactive assistance. It’s a vision that’s becoming increasingly possible as financial institutions combine AI with richer customer insights, an approach reflected in innovations like CSI’s Customer Intelligence Suite.” 

As AI becomes more integrated into banking, how can financial institutions embrace innovation while maintaining customer trust?

“The entire world is trying to figure out what the risks are, which can be absorbed and which we need to avoid altogether. That starts with understanding your own risk posture. You have to know which risks you’re willing to take and which ones you’re not willing to compromise on. 

AI has dramatically shortened the feedback loop. Things that used to take months to learn can now happen in hours or days. That’s incredibly powerful, but it also means you need a culture that’s willing to learn, improve, and keep moving forward. Today, for the really important decisions, you still need humans in the loop. If something goes wrong, you have to be able to stand in front of your customer or your regulator and clearly explain what happened, what controls were in place, and how it could have been prevented. You can’t just hand over the keys.” 

What separates organizations that successfully adopt AI from those that struggle?

“Being comfortable with change is one of the biggest factors. Historically, banking hasn’t always been known for embracing change quickly. Leadership must be visible, and executive teams must be hands-on and become champions for these initiatives. 

There are going to be a lot of people asking for AI tools because the tools are impressive. But don’t fall in love with the tools. Fall in love with the problems you’re trying to solve. 

Everyone is figuring this out together. Be engaged. Be willing to try things. Be willing to fail. Fail fast. Learn from it. Tighten the feedback loop and try again. Visible leadership matters.” 

What should community financial institution leaders be doing today to prepare for the future of AI?

“You have to ‘skate to where the puck is going.’ The pace of change is accelerating. The models available today are dramatically different from what was available even a year ago, and that pace isn’t slowing down. 

If I were running a community bank today, I wouldn’t be thinking only about the state of AI today. I’d be thinking about where customers will be 18 months from now. What happens when someone simply asks an AI assistant to optimize their cash for them? Why are they going to keep their money at my institution? That’s the problem I’d be working feverishly to solve right now. 

I’m bullish on community banks. They’ve gone from competing against the bank across town to competing with organizations on every front. AI gives them an opportunity to compete differently, and I believe that’s exactly what community banks can do.”