February 6, 2026
Recently I have been having numerous discussions revolving around data, AI, and governance for credit unions. So often I remember aspects I should have added afterwards. With that in mind, I’m going to get out of my normal comfort zone. Over the next few weeks, I’ll be sharing a series exploring governance, leadership, and execution that can help credit unions embed data and AI thoughtfully, at scales that match their reality, not someone else’s playbook.
If you join me starting next week, here’s the journey we’ll take together, covering fundamentals while trying to avoid the noise:
- Posts 1–4: Governance foundations and data quality, because these are prerequisites for everything else
- Posts 5-7: AI demystified, what leaders actually need to know, and why AI governance matters whether you build or buy
- Posts 8-9: Leadership and execution, why transformations stall and how to right-size your team
- Posts 10-13: Practical applications, member experience, operations, and governance controls any organization can implement
- Posts 14-16: Strategic positioning, embedding data and AI into business strategy, and what’s ahead
Views are my own and do not represent any employer or board.
