Most credit unions overpay for branches that don’t match how members actually bank. Here’s how to design a smarter, AI-informed, member-centric branch network.
Most credit unions are overpaying for branches that don’t match how members actually bank.
Some locations overperform even though they’re dated. Others are beautiful showpieces with weak traffic and tepid sales. The difference isn’t the furniture or the paint color. It’s strategy — backed by data, and increasingly, by AI.
This matters because branch networks are still one of the largest line items on your P&L. At the same time, digital adoption, remote work patterns, and member expectations are shifting fast as we head into 2026. If your branch strategy isn’t explicitly member-centric and data-driven, you’re flying blind.
Kurt Klassen from LEVEL5 talks a lot about thinking ahead, planning well, building smart, and growing. I’d add one more piece to that formula: use AI to make sure your branch strategy is anchored in real member behavior, not anecdote or habit.
In this article, part of the AI for Credit Unions: Member-Centric Banking series, we’ll look at how to combine traditional branch strategy thinking with AI, analytics, and modern service design so your next branch decision isn’t a guess.
1. Branch strategy starts with one question: who are you serving?
A strong branch strategy begins with a blunt reality check: you’re not building branches; you’re building outcomes for specific members in specific places.
Kurt’s approach at LEVEL5 focuses heavily on understanding your markets. AI just gives you better lenses for that same job.
Use AI to see your market more clearly
Instead of relying only on high-level demographic reports, leading credit unions are feeding multiple data streams into AI models:
- Member transaction data (in-branch, online, mobile)
- Card spend by merchant type and geography
- Geo-coded membership (where members actually live, work, and play)
- Digital engagement (logins, feature usage, chat volume)
- Local economic indicators (growth corridors, employers, housing trends)
From there, AI models can:
- Segment members by behavior, not just age or ZIP code.
- Predict growth pockets — corridors where your type of member is increasing.
- Identify branch catchment overlaps where you’re cannibalizing yourself.
The result is a clearer answer to three questions:
- Which members need physical access most — and why?
- Where are they today, and where will they be in 3–5 years?
- What mix of digital and in-person service do they actually use?
Here’s the thing: most branch networks were built for yesterday’s behavior but funded with tomorrow’s dollars. AI helps you reverse that — fund tomorrow’s behavior with tomorrow’s data.
2. Rethink what a “branch” is in a member-centric world
If you only think of a branch as a big box with teller lines, you’ll miss your best opportunities.
Kurt talks about customizing branch design to your unique service delivery. AI helps you define what “unique” really looks like for your membership.
AI-informed branch formats
Once you understand behavior by market, you can align each location to a specific role in your “service ecosystem” rather than copying a single template everywhere.
Common AI-informed formats:
- Consulting studio: For markets with high digital adoption but complex financial needs.
- Smaller footprint
- Fewer cash stations, more offices and collaboration areas
- Staff trained as advisors, not transaction handlers
- High-transaction micro-branch: For cash-heavy or small-business corridors.
- Compact space
- Efficient self-service plus a small team
- Strong ATM/ITM presence
- Flagship experience center: For core markets and brand hubs.
- Full array of services
- Community and event space
- Financial wellness workshops, small-business hubs
AI models can score each trade area based on:
- Cash intensity
- Business density
- Digital usage
- Product complexity (e.g., mortgages, business loans)
From there, the branch format almost chooses itself.
Service design before interior design
Kurt’s team often talks about service delivery first, building second. I agree 100%.
Before picking finishes or furniture, answer:
- What are the top 5 member jobs-to-be-done in this location?
- Which of those can be handled purely through digital channels?
- Where does human interaction add real value (and revenue)?
Once you map this, AI can help simulate member flows:
- Predict wait times for different staffing models
- Estimate self-service vs. staff-assisted transactions
- Test “what if” scenarios (e.g., add one ITM, reduce two teller stations)
The reality? Most branch remodels overinvest in aesthetics and underinvest in workflow. Member-centric, AI-informed service design fixes that.
3. Use AI to decide where to build, remodel, or exit
Branch placement is where strategy, data, and courage collide.
Kurt’s line — “Challenge yourself to be great” — applies perfectly here. Great doesn’t mean “more branches.” It means the right footprint in the right places with the right purpose.
Location planning: beyond heatmaps
Traditional branch planning leans on:
- Basic drive-time analysis
- Population density
- Competitor locations
That’s fine as a start, but AI-enabled planning adds:
- Granular member migration: Are members moving toward a certain suburb or exurb?
- Employer and commuter patterns: Where do target members go daily or weekly?
- Channel substitution effects: How much branch volume will realistically shift to digital if you exit or shrink a site?
A practical AI-driven approach:
- Score every existing branch on profitability, growth potential, and strategic value.
- Model 3–5 footprint scenarios: consolidate, shift, or expand into new nodes.
- Simulate impact on:
- Member convenience (drive time, walkability)
- Revenue (loans, deposits, fee income)
- Cost-to-serve and staffing
You’re not guessing which low-performing branch to close or which market to enter next — you’re looking at scenario results ranked by member impact and financial outcome.
The role of risk: minimize downside, not boldness
LEVEL5 focuses on minimizing risk while amplifying growth. AI helps you be bold and careful:
- Stress-test branch investments under different rate environments
- Factor in recession or slow-growth scenarios
- Forecast payback periods more accurately
I’ve seen credit unions use this approach to avoid overbuilding in “hot” areas that looked great on paper but had poor long-term member alignment. AI surfaced the mismatch early.
4. Design branches for AI-enhanced member experiences
A branch strategy isn’t just about real estate; it’s about experience. This is where the “AI for Credit Unions: Member-Centric Banking” theme really comes alive.
The smartest credit unions are designing branches that assume AI is part of everyday service — in fraud detection, member assistance, and financial coaching.
AI-powered staff, not AI instead of staff
A modern, member-centric branch combines humans + AI in a visible, helpful way:
- AI-driven CRM insights at the desk:
- Relationship depth
- Next best product suggestions
- Risk or fraud alerts in real time
- Conversation support:
- AI surfaces relevant knowledge-base articles
- Staff get on-screen prompts to ask better questions
- Pre-qualified offers:
- Members sitting down to open a checking account can also see tailored pre-approvals for credit cards, auto loans, or HELOCs
The member feels known, not sold to. The staff member feels prepared, not scripted.
On-site AI channels members actually like
Instead of just adding more screens, use AI where it solves real friction:
- Smart kiosks or tablets that:
- Answer common questions about accounts, cards, or digital banking
- Help members start a loan application, then hand off to a human
- Queue and routing intelligence:
- AI predicts which associate is best suited for each member’s need
- Members get matched to a mortgage specialist vs. a generalist instantly
- Fraud detection in real time:
- High-risk transactions get extra verification steps without slowing everyone else down
Members won’t care that it’s AI. They’ll care that things feel faster, safer, and more relevant.
5. Measure branch performance with smarter metrics
Most credit unions still track branch performance with a limited set of numbers: transactions, accounts opened, balances, maybe NPS.
If you want an AI-informed branch network that’s truly member-centric, you need better questions and better metrics.
Metrics that actually reflect member value
Beyond raw volume, track:
- Member relationship depth by branch catchment
- Product mix shift before vs. after redesign or relocation
- Digital adoption after in-branch education (logins, eStatements, bill pay)
- Cross-channel journeys:
- How many members start digitally and finish in-branch or vice versa?
AI can stitch together these journeys, showing:
- Which branch experiences trigger more long-term relationship growth
- Where friction points push members away from higher-value products
Continuous learning, not one-and-done
Kurt encourages teams to embrace a bold vision. The boldest thing you can do with branch strategy is treat it as an ongoing experiment rather than a one-time construction project.
Use AI and analytics to:
- Compare expected vs. actual outcomes for each branch project
- Adjust staffing, layout, or service mix based on real behavior
- Feed those learnings back into your next location or remodel decision
The reality? A “smart” branch isn’t defined at ribbon-cutting. It’s defined by how quickly you learn and refine once members start using it.
Where AI, branch strategy, and servant leadership meet
One of the themes Kurt mentions is being inspired by servant leadership — serving members and teams first, and letting that drive growth.
AI and branch strategy can feel cold and technical if they’re detached from that mindset. But when you put member needs at the center, data and AI just become sharper tools for serving people better:
- You avoid building impressive branches that quietly drain capital.
- You focus on formats and locations that actually fit how members live.
- You give staff AI support that makes them more human, not less.
For credit union leaders, the next step is straightforward:
- Audit your current network with a member-centric lens: where are you clearly over-serving or under-serving?
- Identify one or two markets where AI-driven analysis could immediately sharpen your branch decisions.
- Pilot a smarter branch concept — small-footprint, advisory-focused, or AI-enhanced — and commit to measuring it ruthlessly.
Branch strategy isn’t about predicting the future perfectly. It’s about being honest about who you serve, using the best tools available, and having the courage to change your footprint when the data — and your members — tell you it’s time.