What are the common risks associated with poorly governed AI systems?
Badly governed AI leads to privacy violations, biased outcomes, leaks of secrets and intellectual property, and weak explainability. It can also be abused by users or attackers. These problems cause complaints, takedowns, fines, and lost deals. Add guardrails, testing, and logs so you can show your work.
Why it matters
Buyers expect responsible use of AI. Lack of proof slows or stops procurement.
Deep dive
Privacy and secrecy: training or prompts may contain personal data or secrets that should not be used.
Bias and fairness: skewed data creates unfair results that harm people and brands.
Explainability: teams cannot explain how the system reached a result.
Security and abuse: prompt injection, data exfiltration, and model misuse.
Recordkeeping gaps: no logs, no version control, no approval trail.
Checklist
Red team prompts and outputs.
Block secret data in prompts and in training sets.
Add bias and performance tests with simple thresholds.
Log decisions and overrides.
Gateway AI use through a single API with review.
Definitions
Prompt injection: a user input that tries to make the model ignore rules.
Explainability: a human readable reason for an output.