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TL;DR:

• Small credit unions are among the most inventive AI adopters, because staff wear many hats and need the help
• Element Federal Credit Union in West Virginia is the small shop Mike points to for AI lessons
• Credit unions copy what works, and their habit of talking to peers speeds that up
• AI now shows up across the whole institution: contact centers, tellers, HR, digital investing, fraud, and board meetings
• Fraud is the worry that hasn't changed in two decades, and good AI now has to fight bad AI
• Mike calls an average member age in the low 50s his top sustainability concern
• He expects 2027 to be a big evolution year for credit union AI

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Before we dive into the key takeaways from this episode, be sure to catch the full episode here:

Small Credit Unions Are Where AI Is Working Best

Mike's view is anecdotal, built from thousands of interviews, and it points somewhere unexpected.

"If you want to look to where AI is being really used really, really well, go to the smaller shops." — Mike Lawson

Necessity drives it. Employees at small credit unions wear so many hats that AI becomes the way they cover more ground. Mike names Element Federal Credit Union in Charleston, West Virginia, led by CEO Linda Bodie, as the place to learn from.

Larger progressive credit unions have a different edge, which is room to fail. They can try something, miss, and try again. Smaller institutions often watch a peer prove an idea first and then adopt it.

Why Credit Unions Copy Each Other So Quickly

Credit unions talk to each other constantly, and Mike says that shapes how technology spreads.

"They're not gonna do anything until they talk to their neighbor or their peer."

Once something works, adoption moves fast. He contrasts this with community banks, where competition means "they don't talk as much." Vendors behave the same way. Fintechs and CUSOs team up to solve one credit union's specific problem and then scale it, a pattern he sees every spring at the NACUSO Network conference. The channel carries bad news as well as good, so he asks credit unions for patience with setbacks.

The SoFi Comparison Behind the Urgency

Mike opens with a claim he says he hasn't fact-checked: SoFi onboarded more customers last year than the whole credit union industry. Public numbers point the same way. SoFi's total members rose from 10.1 million to 13.7 million during 2025, according to its Q4 2025 earnings release, while NCUA reports that federally insured credit unions added 2.4 million. Both are net figures, so treat the comparison as rough.

The system-wide picture is uneven. NCUA counts 4,214 federally insured credit unions serving 146.1 million members, and about 56 percent had fewer members than a year earlier.

"The further that train gets down the tracks, the harder it's gonna be to catch up."

AI Now Reaches Every Corner of a Credit Union

The contact center is the obvious first stop. AI handles the routing-number questions and recognizes the member, so people skip the security-question routine and staff save their attention for hard problems.

"The technology is making you more human and creating a better relationship."

Tellers get the same lift. A question that once meant "let me go talk to Tom down the hall" now gets answered face to face. Mike has also heard of AI in HR and digital investing, and he says boards use it in their own meetings. Two or three years ago the talk was Skynet. Now it's what he calls "the very practical, sometimes boring use cases," and he expects 2027 to be a big evolution year.

Fraud Is the Worry That Never Left

Across two decades, Mike says, fraud has stayed in a credit union leader's top three concerns. AI has made it sharper.

"Since the bad actors are using AI, now the good guys gotta use AI." — Mike Lawson

Fraud sessions at industry conferences are standing room only. For small credit unions that can't build a bank-scale defense, the peer network helps, since working defenses spread by word of mouth.

Getting Younger Is the Survival Question

Asked what credit unions must get right in five years, Mike's first answer is younger membership. He puts the average member age in the low 50s and calls that a long-term sustainability problem. Younger people open accounts at fintechs and invest through apps like Robinhood, and that money leaves. His fixes are bringing digital investing in-house, cleaning up clunky onboarding, and borrowing from SoFi and Chime. Consolidation sits inside the same debate. He sees both sides, and he also wants an easier path to chartering new credit unions.

How This Works in Practice

Mike's contact center example describes the pattern AI handles well. "The AI can handle the really mundane, hey, what's the routing number type of thing," he says, and people step in when the issue is complex. Multimodal's AgentFlow applies that split to credit union back-office work, such as reading and routing loan files alongside the existing loan origination system, so a small team covers more ground.

Want more on financial services and AI? Check other episodes here.

Frequently Asked Questions

Why are small credit unions good at AI adoption?
Small credit unions adopt AI out of necessity. Staff wear many hats, so tools that stretch a small team get used fast, and Element Federal Credit Union in West Virginia is one example.

What AI use cases are credit unions adopting first?
The contact center leads, followed by fraud, teller support, HR, and digital investing. AgentFlow covers the document-heavy lending work that often comes next.

Can AI make a credit union contact center more human?
Yes. AI answers routine requests and recognizes the member, so staff spend their time on the complex problems that need judgment.

How are credit unions fighting AI-powered fraud?
With AI of their own. Fraud is a constant top-three concern, and tools like Decision AI help teams score risk faster.

Why is an aging membership a problem for credit unions?
Because the average member age sits in the low 50s by Mike's estimate, which makes long-term growth hard. Younger people open accounts at fintechs and invest elsewhere.

How should credit unions vet fintech partners?
Start with credit-union-owned structures such as CUSOs. Mike also points to groups that vet fintechs for the industry, including NACUSO, Curql, and Reseda Group.

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