Hype or Reality? 26 Ways Credit Unions Can Use AI to Compete
The Classroom of Innovation cuts through the noise with 26 practical lessons—from A to Z—designed for financial institutions navigating AI adoption in a highly regulated, budget-conscious, trust-driven environment. From fraud and compliance to data, UX, and generational shifts, this framework demystifies where AI delivers measurable value, where caution is required, and how to build sustainable advantage over time.
Artificial intelligence has experienced many boom-bust cycles since its introduction in 1956. One of AI’s founding fathers estimated that by 1965 “machines will be capable of doing any work a man can do.”1 (Quite ambitious in hindsight.)
While AI’s original trajectory was far overestimated, its ability to create heightened operational efficiencies for financial services may yet be underestimated.
So, when it comes to AI for financial services what’s hype and what’s real?
The Classroom of Innovation has 26 lessons – from A to Z – to instruct what’s worth the hype.
Lessons from the Classroom of Innovation
A is for Anxiety. AI anxiety is widespread — not because institutions don’t see the value, but because the rules feel unclear. Fear of retroactive scrutiny can stall progress. The solution isn’t avoidance; it’s transparency, documentation, and human oversight.
B is for Budget. The fight for digital relevancy is about doing more with less dollars. AI tools built for credit unions and community banks can be adopted at a scale that work with – not against – budgets.
C is for Competitive Edge. Combining the heart of “people helping people” with the power of AI in lending and banking sharpens the competitive edge in the digital age.
D is for Data. Data is more abundant than ever – and more fragmented too. AI-assisted connectivity breaks down silos to simplify data across operations.
E is for Expedited. In a high-speed world, patience is limited – especially when it comes to sensitive financial processes like loan approvals. Shifting expectations increase the urgency to integrate AI into banking services like account opening and credit decisioning.
F is for Fraud. Historical cycles of AI show us that every AI boom creates new risk before it creates stability. Last year was the most expensive year of fraud to date and it’s because AI accelerated the arms race. It’s never been more important to leverage AI-powered fraud detection to predict, monitor, and flag anomalies – early and often.
G is for GenAI. Generative AI is excellent at explaining concepts and synthesizing information, but it shouldn’t be making underwriting decisions. Chances are that your teams are already using GenAI for administrative tasks. This familiarity can lay the groundwork for deeper AI integrations.
H is for Hybrid. Hybrid AI isn’t hype: Statistical learning combined with symbolic logic, constraints, and rules is both relevant and needed for heavily regulated industries like ours.
I is for Innovation. Evolving AI is helping financial institutions innovate in ways that were once only for big banks and fintech. Example: cutting down wait times and call abandonments is affordable and accessible with conversational AI.
J is for Journey. Your institution is on a digital transformation journey, not an overnight makeover. The greatest distinguisher of hype is not speed, but sustainability. It’s about choosing technology that compounds value over time rather than chasing the next trend.
K is for Knowledge. At the most basic level, the main attraction of AI is programmable knowledge. The more AI is used for a specific task or function, the more it learns how to do that task effectively and efficiently. This is why it’s a powerful resource to aid - not replace - human work.
L is for Leading Indicators. A back-end feature of AI that delivers front-end results is advanced analytics that indicate clearer foresight and stronger decision-making.
M is for Market Share. Data integrations don’t just deliver a 360-degree view of data; it also expands cross-selling opportunities across indirect lending to grow market share.
N is for Nimble. Over the next several years, traditional institutions will face increased pressure from neobanks and fintechs. Without AI-enabled efficiency, it becomes increasingly difficult to stay nimble and retain market share.
O is for Optimize. History tells us that boom-bust cycles of technology are inevitable. After a year of extremely high portfolio losses, AI is narrowing the operational gap, optimizing areas of greatest need first.
P is for Privacy. Finances are highly sensitive and emotional, especially for borrowers in delinquency. By bypassing human interaction, AI can provide borrowers with greater privacy when correcting past due accounts.
Q is for Quiet. AI isn’t only accountholder-facing. There are many ways (e.g. fraud prevention, compliance, etc.) that artificial intelligence works quietly in the background to make your institution more efficient.
R is for Regulatory Readiness. Financial institutions must consider the regulatory environment before onboarding AI. When investing in AI tools, look for ones that are designed with banking compliance in mind, for example, CECL and UDAAP.
S is for Subprime. Subprime borrowers are more than a number. This rate-sensitive group is prone to rollover loans and repossessions. AI, when used responsibly, can help lenders identify early distress signals, tailor interventions, and reduce losses — without dehumanizing borrowers.
T is for Trust. We are in a trust recession. With more digital access than ever, trust in brands needs to be bolstered – without creating more noise. AI-powered banking can increase data privacy and financial transparency, enhancing trust for the end user.
U is for Uninterrupted. Business continuity planning is not hype. The rise of natural disasters has increased the urgency for planning for interruptions. Smarter AI for call centers levels up the endless phone tree loop to give accountholders real help – no matter the business interruption.
V is for Video. Short-form video is the highest currency in the economy of attention. From marketing to HR to sales, teams need accessible video creation tools. With AI-powered, plug-and-play platforms, video production is a scalable capability.
W is for Withstand. AI is a long game. The AI that is worth the hype is the optimization of one area of the business at a time – strengthening defenses to withstand economic storms.
X is for UX. The user experience (UX) must be a driving factor for implementing AI. But it may be over-hyped. People don’t demand flawless but they do want seamless experiences, one without glitches that cause them to pause their banking journey and reach out for additional support.
Y and Z are for Youth and Gen Z. Only 14% of younger generations use a credit union for their primary banking.2 As older generations age out of primary borrowing years, Gen Z and Generation Alpha (born 2010-2024) will demand personalized, digital-first experiences that can only be delivered through modern technology.
1https://www.ubs.com/microsites/nobel-perspectives/en/laureates/herbert-simon.html
2https://www.pymnts.com/wp-content/uploads/2025/07/PYMNTS-Credit-Union-Innovation-Readiness-July-2025.pdf