If you’re a senior leader at a bank or financial institution and you’re tired of AI conversations that sound impressive but don’t translate, this is written for you.
The AI Mandate takes the position that most AI failure in banking is not a technology problem. It’s a data ownership problem, a political problem, and sometimes a leadership problem. The technology is the easy part.
Who writes this
I’m AJ, a senior AI consultant with 17 years across global banking, financial services, and government. My background includes direct roles at Discover Financial Services, alongside consulting engagements with major US and international financial institutions. The view here comes from inside real engagements not research reports or vendor briefings.
The AI Readiness Triangle
Most AI readiness frameworks talk about data, ROI, and change management; that’s not new, and I won’t pretend otherwise. What I call the AI Readiness Triangle is my own way of organizing what I’ve actually seen break in real engagements:
Data Foundation — does the organization truly own and govern the data the AI depends on?
ROI Clarity — is success defined before the project starts, not retrofitted after?
Change Readiness — will the people who have to use this actually use it, or will it quietly die in a drawer?
Most strategy documents assume all three are solved. In my experience, at least one almost never is.