AI governance is a governance framework that regulates who gets to decide what, who is responsible, and how to monitor AI in the business — to use AI effectively without losing control. Zenify records AI conversion of +21% (approved).
TL;DR
- AI governance regulates rights, responsibilities, and supervision.
- Designate who is responsible for each AI system.
- Decentralization: AI can decide what to do, what needs to be approved by someone.
- Logging to trace errors.
- Periodically check for fairness, security, and quality.
What is AI governance?
AI governance is a set of rules and processes that govern how AI is used: who is configured, what AI can decide, who must approve, how to monitor, and how to handle AI mistakes. Without governance, AI runs "masterless" — a huge risk.
5 components of AI governance
1. Responsible person
Clearly assign owners to each AI system.
The person who is ultimately responsible when AI is wrong (see AI Ethics).
2. Decentralization
Jobs | DIY AI | Need reviewer
Answers to frequently asked questions | Yes | No
Compensation Commitment | No | Yes
Big Discount | No | Yes
Personal information | No | Yes
3. Logs and tracing
Record questions, answers, decisions.
Can be traced back when an error occurs.
4. Quality monitoring
Sample answers and score them.
Early detection of false AI (see AI fabrication).
5. Check periodically
Fairness, security, compliance with regulations.
Update when the process changes.
Building AI governance for small businesses
Step 1: Write short principles
Who is in charge, what AI can do on its own, what needs people.
Step 2: Clear delegation of authority
List AI decisions and tasks that need to be approved.
Step 3: Enable logging
Record AI activity for tracing.
Step 4: Monitor and meet periodically
Measure quality, review and adjust.