By Barb Lowman, CUDE, President, CUNA Strategic Services
Remember just a couple of years ago when artificial intelligence was a futuristic concept, contained within a few niche industries and the occasional sci-fi film? Fast-forward to today, and just about every conversation I have with credit union leaders includes some discussion of AI: Which technologies should we be using? Are we behind in AI adoption? How much is hype and how much is reality?
While none of us have a crystal ball, the question is no longer whether AI will matter, but how to adopt it thoughtfully, affordably and in alignment with cooperative values.
A recent study by Wipfli (a CSS alliance provider) found that AI adoption is accelerating, but AI maturity isn’t keeping pace. Two-thirds of respondents (66%) said their credit unions are actively implementing AI solutions, but only 16% reported having a roadmap that includes governance frameworks and measurable business impact.
We all know that the credit union industry is diverse, and so is technology adoption and maturity. While some credit unions are investing in AI startups and leading the innovation charge through early adoption, many credit unions still rely on outdated digital platforms, impacting their ability to modernize the member experience. McKinsey estimates that three-quarters of credit unions are still using clunky legacy loan origination systems with little to no automation.
So how do we go from dealing with dated systems to implementing cutting-edge AI solutions?
Across credit unions, AI initiatives tend to cluster around three primary objectives.
1. Automating repetitive employee tasks.
Operational efficiency remains a compelling entry point. AI tools are being deployed to modernize back-office operations, reducing manual workloads and unifying disconnected systems. From scanning and indexing documents, to retrieving information from multiple systems, drafting routine communications, and assisting staff with research, these tools help credit unions operate smarter and faster while maintaining the human touch that defines their member relationships. For many institutions, internal productivity use cases represent the lowest-risk starting point.
2. Enhancing member experience.
Member expectations are shaped by digital-first experiences across industries. AI enables greater personalization, faster response times, and more intuitive self-service tools. Generative AI in contact centers (from chatbots to AI voice agents to real-time agent support) illustrates how technology can reduce wait times for simple requests and take pressure off human teams.
Recent industry research supports this idea. According to the 2026 State of AI in Financial Services report from NVIDIA, 42% of the top AI use cases across financial institutions center on customer experience and engagement – the largest single category. This aligns with findings from Cornerstone Advisors, which reports that 74% of credit union respondents plan to implement generative AI in their contact centers by 2026.
3. Strengthening compliance and risk management.
Cost discipline matters. Some AI platforms are prohibitively expensive, particularly enterprise-grade solutions marketed to large banks. Credit unions must evaluate total cost of ownership, including integration, training, governance, and ongoing monitoring. The strongest candidates are those that reduce operational expense, mitigate regulatory risk, or materially improve member retention and growth.
Start with the problem, not the technology. AI is not a strategy in itself. Leaders should resist adopting tools simply because competitors are doing so. Identify and prioritize specific pain points: Is your contact center experiencing long hold times? Are compliance teams overwhelmed by manual reviews? Is staff time consumed by repetitive documentation tasks? If the problem is clearly defined, the efficacy of an AI solution can be properly evaluated.
Avoid band-aid stacking. One common risk is having multiple departments implement different AI solutions without consulting each other, often layering point tools on top of legacy systems. Over time, this creates operational complexity, fragmented data, and inconsistent user experiences. A more sustainable approach is to coordinate AI initiatives across the organization and align them with your broader digital transformation strategy, ensuring tools integrate cleanly and support long-term architecture and governance goals.
Establish a governance rulebook. Even before enterprise-wide AI adoption, employees may experiment with generative AI tools, creating security, privacy, and reputational risks. Credit unions should develop clear policies covering data sharing, member confidentiality, and approved platforms. The NCUA provides guidance through letters like 07-CU-13 and 01-CU-20 to help implement vendor oversight, maintain compliance, and protect member data. Don’t think of governance as a barrier but as a shield.
Despite the noise surrounding AI, its impact on financial services is still in the early stages. Many institutions are still piloting use cases rather than operating at scale. Workforce readiness is also developing; a recent LinkedIn study found that only 2% of professionals in financial roles report having AI skills. If your organization feels “AI illiterate,” you are not behind – you are in line with the broader industry. The opportunity lies in education and incremental capability building.
Board members and executives should view AI literacy as a leadership competency. Of course, that doesn’t mean every leader must become a data scientist, but it does mean understanding core concepts, risks and strategic implications to ask informed questions and guide investment decisions.
Credit unions have a unique opportunity in the AI era. Unlike shareholder-driven institutions, credit unions can adopt technology with a singular focus on member value, to deepen relationships, protect member assets and strengthen operational resilience.
Start small. Pilot thoughtfully. Build governance early. Invest in staff education. And, of course, ensure every initiative ties back to your mission. AI is reshaping financial services, and for credit union leaders, the goal is not to move fastest but to move wisely, responsibly and with members at the center.
Want to discuss your technology strategy? CUNA Strategic Services specializes in guiding credit unions through the selection and implementation of fintech partnerships for long-term sustainable growth. Get in touch with our team, and let’s chat about how we can help your organization.