AI governance starts with data foundation, builds from there
A report from TechTarget argues that effective AI governance depends on getting the underlying data infrastructure right before layering on broader oversight frameworks.
Why this matters: Most AI governance talk jumps straight to algorithms, audits, and policy. But the data underneath the model is where the real decisions get made. What data was collected, from whom, and how it was stored determines what the AI learns and who it can harm. If the foundation is bad, no governance framework built on top of it will fix that. Getting data practices right is not a technical detail. It is the actual starting point for accountability.
Who should care: AI governance · Lawyers · Administrators · General readers · Policy
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