Industry Reports: Could AI Give Smaller Credit Unions a New Kind of Scale? These Folks Think So.

​AI could prove especially consequential for smaller and mid-sized credit unions because it offers something they have historically struggled to buy: scale without a corresponding increase in headcount.

By Marc Rapport
Contributing Editor

Key Points

• AI can help smaller credit unions scale expertise and productivity without adding specialized staff across every department.
• Early opportunities include internal knowledge management, lending support, fraud detection, member service and repetitive back-office processes.
• The greatest gains may come from integrating AI across workflows while maintaining governance, human oversight and the personal service members expect.

Smaller credit unions confront many of the same regulatory, technology, fraud, lending and service demands as institutions many times their size, but they have fewer people to divide among those responsibilities.

That makes AI’s ability to multiply employee capacity potentially more significant for a smaller credit union than for a bank already equipped with large teams of analysts and specialists.

Linda Bodie

Linda Bodie, CEO + Innovator at Element FCU in Charleston, WV, sees AI as a way to put capabilities resembling an analyst, researcher, writer and administrative assistant within reach of each of the 15 employees at her 4,375-member cooperative.

“For small credit unions, AI isn’t primarily about replacing people. It’s about giving good people more capacity,” said Bodie, who has been at the helm of her Mountain State shop since 1998 and seen its assets grow to about $47.5 million.

Todd Link, chief member services officer at $3.5 billion Dupaco Community Credit Union, joined the Dubuque, Iowa-based cooperative in 2014 and sees that AI-driven capacity emerging particularly in operations, where those tools can take over work that does not depend on the personal relationships at the center of the credit union model.

“At this time, I see AI as one of the leading ways credit unions of any size can find back-office efficiencies,” said Link, who oversees member services for 182,000 members and its 616 employees.

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Catherine Wright

Extending Expertise Without Extending Payroll
Catherine Wright, a consultant for Cornerstone Advisors focuses primarily on strategy, operations, governance and, most recently, AI, for her Arizona-based advisory and research firm.

Wright said recent research conducted with The League of Credit Unions & Affiliates and its LEVERAGE solutions provider found internal productivity and knowledge-management tools already helping employees work more efficiently.

Larger institutions can hire more specialists and dedicate larger teams to functions including marketing, fraud, lending and member support, while smaller shops must stretch existing employees across those responsibilities. “AI is going to help the smaller institutions close some of this gap by extending the capacity of their existing employees,” Wright said.

Laura Ernzen, the league’s chief innovation officer, joined the organization in February 2024 and has served in her current role since then, helping lead innovation and growth initiatives through LEVERAGE, the service corporation for the league that serves credit unions in Florida, Alabama, Georgia and Florida.

“It’s not about replacing people. It is about helping employees spend less time on administrative work and more time delivering value to members,” Ernzen said.

More AI News From Industry Reports:

• How AI Is Reshaping Credit Union Operations
• AI Moves From Monitoring to Managing Compliance Workflows​

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Laura Ernzen

Starting Where the Risk Is Lower
The most practical entry point may not be an autonomous lending engine or another highly visible member-facing deployment, but internal knowledge management where employees can search policies, procedures and operational guidance or draft and summarize documents.

Wright said those applications can introduce employees to AI while limiting some of the concerns surrounding sensitive member information and automated decisions.

“Enterprise knowledge management is going to be the best use case, I think, to start off with,” the Cornerstone consultant said, noting that employees also need time to learn prompting, understand AI’s limitations and become comfortable verifying its work. The experience can build confidence before a credit union expands into applications involving member data, lending, fraud or other higher-risk activities.

Bodie said she would also begin with a secure AI employee and operations assistant connected to policies, procedures, product information and selected core data, allowing employees to find answers, understand member relationships and identify missing information.

“Employees should be able to ask a secure internal assistant how to complete a process, what a policy requires or what steps apply to a particular member situation without searching through multiple manuals and folders,” the Element CEO said.

Moving AI Into Lending and Member Service
Lending was cited as an area that shows how AI could improve speed without transferring the ultimate decision away from people, since much of a loan’s processing time is consumed by collecting documents, entering information, calculating income and identifying missing items.

Wright said AI can review submitted documentation, flag missing signatures, analyze financial statements and prepare summarized information before a credit union employee makes the final underwriting decision.

Bodie sees similar potential in having AI read pay stubs and tax documents, calculate debt-to-income ratios, summarize credit reports, identify policy exceptions and organize underwriting packages. “AI shouldn’t replace the lender’s judgment. It should make sure the lender spends more time using judgment and less time moving information from one place to another,” she said.

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Todd Link

Link at Dupaco said agentic AI can push that support considerably further while operating continuously behind the scenes. “Agentic AI has the ability, depending on the credit union and its desire to leverage the technology, to support a loan from end to end 24/7, or to review unusual transactions in real time and close a card, order a new card, start a dispute, and provide status updates on delivery,” he said.

Combining Automation With Human Advantage
Member service presents a similar balancing act because AI can answer simple questions, authenticate callers and direct inquiries without tying up employees, yet members may still want a person when the interaction becomes more complicated.

Cornerstone’s Wright said some credit unions are finding a hybrid model more effective than attempting to automate the contact center completely, particularly for members uncomfortable with extended conversations with an AI agent.

That distinction reinforces an advantage smaller credit unions should be careful not to automate away: relationships built on trust, flexibility and employees who understand their members. “The winning model isn’t AI instead of people. It’s human service made faster and smarter by AI,” said Bodie, the longtime innovations leader at Element.

Ernzen at the League of Credit Unions & Affiliates similarly sees AI helping smaller institutions respond more quickly, personalize communications, identify potential fraud and make specialized knowledge available across the organization while preserving personal service.

“Smaller credit unions already have an important advantage: strong member relationships,” she said. “AI can help them preserve that personal service while operating more efficiently and effectively.”

Orchestration Could Determine the Payoff
Affordability remains a central question because smaller credit unions generally cannot build proprietary AI platforms or maintain large technical teams, and adding separate vendors for every application can create its own cost and management problems.

Wright recommends checking first with existing providers for AI capabilities already available or planned, then beginning with one or two high-value use cases and establishing governance before expanding.

CUSOs, core processors, associations and other shared-service partners could also make sophisticated tools affordable by spreading development, security, integration and compliance costs across institutions.

Bodie said smaller credit unions need secure integrations, permission controls and audit trails, but they do not necessarily need to own the underlying technology: “Small credit unions don’t need to own the technology. We need affordable access to the capability.”

Link believes the larger opportunity ultimately lies in connecting agents rather than purchasing isolated AI features that remain trapped inside individual applications.

“The power of a bot will only ever be that bot. But the power of a dozen bots creates exponential value,” the Dupaco executive said, arguing that orchestration can spread AI across many tasks, lower cost per use and reduce the burden associated with governing numerous disconnected deployments.

Broadly speaking, he said, “These are not technologies of tomorrow; they are available and being leveraged today by determined credit unions leaning into AI.”

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