Over the next seven years, artificial intelligence will reshape credit unions from the inside out. Not just the products members see, but the roles, workflows, and org charts behind them. This new, seven-part series will break down the AI trends we believe every credit union leadership team should be tracking, each grounded in research and mapped to the priorities that matter most to your institution: job displacement versus job creation, member expectations, business model impact, regulation and public sentiment, and infrastructure demands.
We’re starting with the trend that sets the stage for everything else: the work your people do every day is, statistically speaking, some of the most exposed work to AI in the entire economy.
The Big Picture
In January 2024, the International Monetary Fund published one of the most-cited analyses to date on AI and labor markets. The topline number got most of the attention: almost 40 percent of global employment is exposed to AI, a share that rises to 60 percent in advanced economies, notably, where credit unions operate.
Among those exposed jobs in advanced economies, the IMF found the outcomes split roughly down the middle: about half could see AI take over tasks currently done by people, while the other half stand to benefit from real productivity gains through AI-augmented work. In other words, exposure isn’t destiny. It’s a fork in the road, and which path an institution takes depends heavily on decisions made now.
Why This Lands Squarely on Credit Unions
Here’s the part that should get your credit union’s attention, specifically: the IMF identified cognitive-intensive, non-routine work as the category most exposed to AI. That description is not a stretch for credit union staffing; it’s a job description.
- Loan officers evaluating applications
- Compliance staff reviewing documentation
- Member service representatives handling inquiries
- Analysts running reports
- Back-office processors managing transactions
Every one of these roles fits the high-exposure profile the IMF described. This matters because of what kind of automation this is. Prior waves of automation, robotics, assembly lines, and industrial machinery largely bypassed knowledge work and left it to expand. This wave is different. AI is built specifically to replicate, accelerate, or eliminate the kind of judgment-based, document-heavy, conversational work that fills a credit union’s org chart.
The Two Questions Every Credit Union Should Be Asking
This creates a strategic fork for credit union leadership that will only get sharper over the next seven years.
The operational question: Which of these roles will AI handle better, faster, or more cheaply than a person, and what does that mean for staffing levels, training investment, and how teams are structured going forward?
The cultural question: Credit unions have built their identity on the human relationship. The fact that a member is part of a community and not just an account number. If AI takes over the transactional work that currently surrounds that relationship, such as the paperwork, the routine inquiries, and the report-running, does the member relationship get to go deeper? Or does the institution start to feel like just another digital-first competitor with a friendlier name?
There’s no universal answer. But the credit unions that treat this as a strategic question now, rather than a staffing problem to solve later, will be the ones that come out the other side stronger and with a clearer vision for the future.
That’s the frame for this entire series. Part two will dig into what “job displacement vs. job creation” actually looks like in practice inside a credit union, and where we think new roles are likely to emerge.
Ready to plan? Let’s connect.
This is Part 1 of a seven-part series from Seez on AI trends shaping the credit union industry. Part 2 continues our look at the internal consequences of AI for credit union operations, staffing, and competitive positioning.
References
IMF Staff Discussion Note SDN/2024/001, “Gen-AI: Artificial Intelligence and the Future of Work,” January 2024. https://www.imf.org/-/media/files/publications/sdn/2024/english/sdnea2024001.pdf