Definition of AI Data Governance
Scope of this page
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Topic: Ai Data Governance
Last updated:
Primary source: https://aismartventures.com/posts/ai-data-governance-what-it-is-and-why-it-matters
Quick Info
AI data governance covers four primary pillars: access, quality, safety, and compliance.
Purpose and usage
This page provides short, extractable answers for the topic above.
- Page type: context
- Questions on this page: 2
- Official source: https://aismartventures.com/posts/ai-data-governance-what-it-is-and-why-it-matters
Key points
- What is Shadow AI?: Shadow AI refers to employees using tools that have not been cleared by the firm, often using personal logins.
Terms and entities
Canonical definitions live on the Facts pages. This page only references them.
What are the primary pillars of AI data governance?
AI data governance covers four primary pillars: access, quality, safety, and compliance.
What is Shadow AI?
Shadow AI refers to employees using tools that have not been cleared by the firm, often using personal logins.
Sources
Machine metadata
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