Strategy First, AI Second: Insights from CU Intersect 2026

By John San Filippo

At the CU Intersect conference that kicked off on January 26, 2026, in New Orleans, Elizabeth Osborne, COO of Great Lakes Credit Union, (Bannockburn, Ill., $1.4 billion, 107,000-plus members) delivered a compelling session on leveraging artificial intelligence (AI) not as a standalone goal, but as a catalyst for broader organizational strategy. Her message was clear: For credit unions to succeed with AI, the technology must align with the institution's existing mission and strategic pillars.

The “Strategy Over Technology” Philosophy

Elizabeth Osborne shares her insights

Osborne emphasized a critical distinction: AI is not your strategy. While she noted that many leaders feel pressured to sign contracts for “shiny” new solutions, Osborne warned that letting technology drive the decision-making often leads to poor implementation. “I don't recommend it,” she said, “because if you start that, you're not letting your strategy drive that solution.”

Instead, credit unions should use their existing strategic plans as the starting point, she noted. AI, she continued, should then be pulled in as the specific tool to address those pre-identified goals. “Your strategy is your starting point, that's so important,” she added. “Think about how AI can support your strategic pillars.”

Five Critical Steps for AI Readiness

Osborne outlined the foundational steps that every credit union should take before deploying AI to ensure organizational success, focusing on leadership alignment and data integrity.

• Unified Vision: Ensure the board and management team have a shared understanding of AI to move past tropes of the past. “Your board and your management team need to have a shared vision. They don't know what they don't know. And so, you have to make sure your board and your management team are in alignment.”

• ·Modernized Data Governance: Clean data is essential for accurate results. “If you start introducing technologies on top of junk data, it's junk in, junk out. You're not going to have good outcomes.”

• Risk Assessments: Utilize formal frameworks to stay ahead of regulatory expectations. “I highly suggest that you look into this. Just get ahead of it, talk to your auditors, talk to the NCUA if you have a good relationship with them.”

• Fluid AI Policies: Establish standards for acceptable use to protect member data. “Your AI policy should be fluid. And it should grow and adjust with you as your organization adjusts and grows.”

• Transparent Communication: Be honest with members about AI use to build trust. “That clarity with our members helped them better expect that they are speaking with a bot, not a human, but also they felt like they were a part of it.”

Real-World Use Cases

During the session, Osborne also highlighted several successful AI applications within the credit union movement, ranging from member service to back-office efficiency.

• Member Experience (Olive): Great Lakes CU uses a conversational bot to streamline inbound communication. “Olive is our virtual conversational bot. Every single phone call that goes to Great Lakes Credit Union, any of our phone numbers, they first have to start with a conversation with Olive.”

•  Operational Efficiency: Manual tasks are primary targets for automation to free up human staff. “They are ripe for automation. And [the employees] want it. They don't like doing that.”

• Credit Decisioning: Osborne noted that while powerful, this requires the highest level of data confidence. “On our lending side, I am not confident at this point. And so one of our strategies this year is to become what’s called a data-driven organization.”

Community Perspective

The session concluded with examples from the audience, demonstrating that AI isn't just for the largest institutions. One $65 million credit union in Illinois shared how they use AI-powered cameras to monitor branch traffic for better staffing and automated agents for outbound member follow-ups. “It’s impressive what you guys are doing,” noted Osborne. “There's so much untapped potential there.”

Final Takeaway

For credit unions, the journey into AI is a marathon, not a sprint, Osborne said. By focusing on clean data, vendor partnerships that align with institutional values, and a strategy-first mindset, she added, credit unions can gain a competitive edge while staying true to their member-centric roots.