Harnessing AI and Automation: Practical Use Cases for Community Banks

The current buzz around using Artificial Intelligence (AI) is loud in just about every business sector out there. For financial institutions, both AI and automation matter a lot when you’re talking about profitability and long-term success. However, banks – especially community banks – have some unique challenges to consider when they begin seeking to implement AI and automation. With typically limited resources and specific guard rails related to privacy and security, banks must focus on foundational readiness and their approach should be strategic, not reactive. The goal is not to implement technology for its own sake or to keep up with other banks, but rather to meaningfully solve problems within the institution’s strategic mission.

PRI’s Strategic Operations Manager Kevin Cruse recommends going back to basics and getting very practical to achieve sustainable success with AI and automation.

AI vs. Automation for Operational Leaders

First, Cruse said it’s important to understand the key differences in functionality and purpose between the two. Automation doesn’t really “think” in the same way AI does. Instead, the user builds rules around repetitive processes, and the automation program performs the function according to the rules that are set for it. This frees humans from repetitive tasks, and it performs with speed and consistency. Most banks are using this technology to increase their operational efficiency and profitability. 

On the other hand, Artificial Intelligence is designed to think, learn and adapt. The user feeds it dialogue, text, images and questions, and it can analyze patterns and make predictions. As AI is used and fed more data – if that data is accurate anyway – it gets “smarter” and becomes better at analyzing and predicting over time. There are many ways to begin implementing AI, but a solid foundational readiness that considers proper AI governance, process maturity and data quality is crucial. AI should not be implemented without the proper groundwork. 

Cruse recommends starting with automation, which is lower risk and delivers a higher ROI while building process discipline. Dipping a toe into the AI waters by trying assistive AI tools to summarize emails for instance, serves as a low-barrier entry point. 

“Accessible AI tools like Microsoft Copilot provide a practical way to explore AI without a big tech investment,” Cruse said. “These are a great way to leverage AI in areas where it supports the team but doesn’t overwhelm the organization with too much, too soon.” 

Where to Start: High-Impact, Low-Lift Opportunities

When prioritizing use cases for AI and automation, Cruse recommends analyzing the following criteria:

• Clear pain point alignment. Leaders should ask, “What is the problem we want to solve and does this solution align?” 
• Measurable ROI. You will want to be able to show a clear and measurable return on investment, especially if you are purchasing an expensive solution. Does the problem warrant the financial investment in the solution?
• Feasibility and low complexity. Is the solution easily implemented into your operations? Who will “own” the implementation? Is it easy to train employees to use?
• Fast time-to-value. Will you see a quick return on your investment?

Some examples of strategic places to implement automation and light-touch AI include:

• In the back office. Using a light-touch AI solution that likely already exists to automate manual, highly repetitive tasks like document routing, approvals and reporting will positively impact overall operational consistency and operational efficiency.
• With the staff. Help your team work smarter, not harder, by implementing assistive AI applications like email management, summarization and drafting. You don’t need a full technology team to manage these tools, and they ensure that the community bank in particular preserves the high touch model it’s known for while freeing the staff from low-value, repetitive tasks.
• With the customer. AI-assisted triage and intelligent routing that gets inquiries to the right person faster supports customers and improves their overall experience with the bank.

Balancing Operational Efficiency with Personalization

Using automation to remove friction behind the scenes and AI as a tool to enhance, not replace, personal service is the way to reset how you do business. Community banks build their reputation upon their responsiveness and trust in the community. AI and process automation tools, when used correctly, free up employees to focus on what’s important and do what they do best – serve their customers.

“Using these tools thoughtfully and correctly allows a shift in mindset from ‘automation for replacement’ to ‘automation for enablement,’” Cruse said.

The Role of Partners and Platforms

There is a difference between transactional tools and strategic partners, according to Cruse. There is a growth of low-code/no-code platforms which makes process automation and AI tools more accessible, but there is also value in finding the right strategic partners who will assist with long-term foundational planning.

“Expanding accessibility and building trust in these tools provide the building blocks for taking the next step and the next one,” Cruse said. “Finding a partner to walk through aligning these tools with the bank’s strategic perspective makes a world of difference. That’s the kind of support most valuable in helping banks adopt AI most successfully.”

Upskilling and Internal Capability Building

In the PRI article AI and Automation in Community Banking, PRI Director of System Evaluation Mike Neale emphasizes the importance of hiring talent with AI skills. He notes that AI will impact community banks across the organization from marketing to loan underwriting, from operations and IT to customer experience, and from HR to the teller line. With that in mind, he suggests that it is critical that financial institutions begin sourcing leadership positions focused on AI and consider AI skills as a part of all talent acquisition. In addition, firms can train employees internally using widely available free content or partnering with experts.

Cruse agrees and says now is the time to build AI literacy across existing teams using available training platforms such as LLM (large language model), prompt engineering and vendor education.

“This doesn’t mean you have to build out a full AI department, but it’s wise to begin embedding continuous learning into your existing culture and operations,” Cruse said. “Encourage cross functional learning and begin demystifying this technology. The goal is to become informed users first. In addition, start now to build a playbook that sets the guidelines for the ways in which banks should and should not work with AI.”

Looking Ahead: What’s Next in AI for Community Banks

Cruse said real opportunities lie in quiet transformation, not flashy tech, and embedded intelligence in workflows supports better decisions. It’s easy to start with low-code, no-code AI add-ons to enhance human decision making without a massive infrastructure investment.

“There is no shortage of shiny new tools out there, but the real impact occurs when they are applied selectively to solve real world business problems,” Cruse said. “Stay aligned, be intentional, and focus on meaningfully solving problems and addressing pain points. That’s the way to be successful in this arena.”

About our experts

Kevin Cruse brings 20 years of banking experience to PRI from his time with large regional banks and within the farm credit system. As a skilled manager, Kevin utilizes process engineering, banking strategy, operations, automation, and data background to support and build teams to enhance their overall productivity and efficiency with the organization. He has led teams in various initiatives in the banking industry from the build-out and enhancement of card and dispute teams and operational services to standing up data strategy, quality, and remediation programs where they had not previously existed. Kevin has diverse and expansive experience across the financial industry with a proven track record of increasing productivity, reducing costs, and managing risk for the organization.

Resources

AI and Automation in Community Banking – PRI

The Human Touch in Digital Banking: Balancing Automation and Personalization – PRI 

PRI specializes in identifying profitability improvement areas for financial institutions through revenue growth, cost control, streamlining processes, and effective use of technology. Contact us to learn more about our personalized approach to propel growth and improve profitability.