AI + analytics = value? (2/2) - why are we still having problems getting the data foundation right. (And does it really matter?)

The article argues that AI value does not require a perfectly complete data foundation, but it does require clear governance, business context, and measurable use cases. For CIOs and technology leaders, the strategic takeaway is to use AI first for bounded exploration—such as validating data quality, surfacing gaps, and testing scenarios—then shift successful workflows to deterministic systems to reduce cost, variability, and deployment risk. IT organizations should prioritize use cases with strong telemetry and business outcomes so they can distinguish data issues from model issues and prove ROI before scaling.