THE REAL AI CONVERSATION COMMUNITY BANKS NEED TO HAVE

If you’ve attended a banking conference lately, you’ve probably heard the same message over and over: adopt AI now or risk falling behind.

There’s certainly truth in that. AI is creating new opportunities to improve efficiency, streamline processes, and help bankers focus on higher-value work. But amid all the excitement, some important questions often get pushed aside. Questions about ownership, risk, regulation, and people.

At Bankers’ Bank, we’re embracing AI ourselves. We’ve implemented Microsoft Copilot across our organization, explored AI tools that support our software development teams, and created an employee workgroup where staff can share successes, lessons learned, and ideas. Our goal isn’t to have all the answers. It’s to learn together, build practical expertise, and have honest conversations about what AI means for our industry.

With that in mind, here are three topics we believe community bankers should be talking about more often.

1. AI Can Write Code. But Who Owns It?

One of the hottest topics in AI today is AI-assisted software development, sometimes called “vibe coding.” The concept is simple: describe what you want, and AI generates the code for you.

It’s impressive technology, and it can be a valuable tool. But there’s a question many banks need to consider: if AI writes the code, who is responsible for making sure it’s secure, reliable, and appropriate for your institution?

Many community banks don’t have dedicated software development teams. That’s not a problem until organizations begin creating or modifying software without having the expertise needed to review and validate the output.

Think about it this way: you wouldn’t let AI approve loans without a qualified lender reviewing the decision. The same principle applies to software development. Human oversight remains essential.

For AI-generated code, the “human in the loop” isn’t simply someone who understands the business process. It’s someone with the technical experience to evaluate the code, identify security concerns, and take responsibility for the final product.

The good news? The solution isn’t complicated.

Banks should have a strong Software Development Lifecycle (SDLC) in place before pursuing AI-assisted development. Whether software is written by an employee, a vendor, or AI, it should follow the same planning, testing, approval, and maintenance processes. If those capabilities don’t exist in-house, consider partnering with a trusted third party to help review and manage AI-generated solutions.

The technology may be new. Sound governance is not.

2. Regulations Are Still Catching Up

Another challenge banks face is the lack of comprehensive regulatory guidance specific to AI.

While regulators have provided direction on topics such as model risk management, third-party oversight, and cybersecurity, the industry is still waiting for more detailed expectations around AI governance.

That doesn’t mean banks should delay planning until formal guidance arrives.

In fact, now is the ideal time to establish a framework that can guide your institution’s approach to AI adoption. A well-defined framework helps create consistency, identify potential risks, establish controls, and document decision-making before new tools become deeply embedded in your organization.

Several frameworks are worth considering, including:

• NIST AI Risk Management Framework (AI RMF): A widely respected framework designed to help organizations identify, assess, and manage AI-related risks.
• CRI Financial Services AI Risk Management Framework: Developed specifically with financial institutions in mind and aligned with NIST principles.
• ISO/IEC 42001: An international standard focused on AI management systems and governance.
• FFIEC and Interagency Guidance: Existing regulatory expectations around model risk and third-party risk that can help support AI oversight efforts.

The most important thing isn’t which framework you choose. It’s having one.

And if you’ve already started using AI without a formal framework in place, don’t panic. A framework can be used just as effectively to assess existing AI initiatives, identify gaps, and strengthen governance going forward.

The institutions that establish strong guardrails today will likely be better positioned when future regulatory expectations become more defined.

3. Don’t Overlook the Human Side of AI

Perhaps the most important conversation is also the one discussed the least.

AI can save time. It can automate repetitive work. It can help employees become more productive.

But what happens when someone’s favorite part of their job is the work AI is now helping perform?

For many bankers, expertise isn’t just what they do. It’s part of their professional identity. Whether it’s underwriting loans, analyzing financials, reviewing compliance exceptions, or solving customer problems, years of experience have helped shape their careers.

When AI enters the picture, leaders need to be thoughtful about how those roles evolve.

The goal shouldn’t be replacing expertise. It should be elevating it.

A few ways banks can help accomplish that include:

• Reframe the Role
  Position experienced employees as decision-makers, reviewers, and advisors. Their judgment remains critical, especially when AI outputs require context, interpretation, and accountability.

• Recognize New Skills
  Reviewing AI-generated insights, identifying exceptions, and applying human judgment are valuable skills. Make sure those contributions are acknowledged and rewarded appropriately.

• Invest in Relationships
  One of AI’s greatest benefits may be the time it gives back. That time can be redirected toward the activities that have always differentiated community banks: building customer relationships, strengthening communities, and delivering personalized service.

Technology can support those efforts, but it can never replace them.

Moving Forward with Confidence

Let’s be clear: this isn’t an argument against AI.

At Bankers’ Bank, we believe the opportunities are real. AI can help organizations work more efficiently, make better use of information, and create capacity for higher-value work.

But successful AI adoption isn’t about chasing the latest trend. It’s about balancing innovation with the principles that have always guided good banking.

That means maintaining ownership and accountability, even when AI helps create the work product. It means implementing sound governance before regulators require it. And it means using technology to enhance human expertise rather than diminish it.

The banks that get AI right won’t be the ones moving the fastest. They’ll be the ones combining innovation with sound judgment.

As a bank built to serve banks, that’s the approach we’re committed to taking, and the conversation we’re committed to having. We look forward to learning alongside the community banking industry as AI continues to evolve.