What is AI governance and why is it important for businesses?
AI governance is how you decide, document, and defend the way AI is designed, deployed, and monitored. Good governance reduces legal and brand risk, speeds enterprise deals, and keeps models aligned with your goals.
Why it matters
Without governance, AI projects stall in procurement, drift in quality, and create privacy and ethics issues that are hard to unwind.
Deep dive
Ownership: a named executive sponsor and a product owner.
Use case register: an inventory that lists models and assistants, data sources, purposes, and risk tiers.
Policies and guardrails: permitted uses, red lines, sensitive data rules, and human in the loop.
Testing: accuracy, bias, robustness, and prompt red teaming.
Monitoring: drift, abuse, and performance, plus logs for decisions and overrides.
Vendors: contracts, DPAs, and boundaries on logging and retention.
Checklist
Name owners and publish who is responsible and accountable.
Create a use case register and risk tiers.
Write short policies that teams can follow.
Add tests for high risk uses and log exceptions.
Monitor, retrain, and review each quarter.
Definitions
Human in the loop: A human reviews or can override important AI outcomes.
Drift: A change in model performance as data or usage shifts.