Across the credit union industry, many AI pilots underperform or stall. The issue rarely comes from the technology itself—most tools work as advertised. The real barrier is that AI gets layered on top of an existing process that needs to be redesigned. Take AI document reading: a credit union buys the tool, validates that it extracts data correctly, and then teams continue reviewing every file manually “just to be safe.” Staff follow the same checklists, open the same PDFs, and layer automation on top of old habits—producing extra work, limited efficiency gains, and confusion. 

This session reframes the problem: rather than debating which AI tool is best, it focuses on how to build a process where automation can replace work. You’ll learn a five-step method and review a client example processing more than 50,000 applications a month, reaching 82% automated document processing in six weeks.