Why governance matters (especially for SMBs)
- Vendors change fast—policies keep data and actions controlled.
- Stakeholders need proof of safety—logging and approvals provide it.
- Regulation is rising—prepare now with light but real guardrails.
The minimum viable AI policy
Scope: Allowed use cases, forbidden actions, and refusal rules.
Data: What data can be used, redaction, and retention.
Vendors: Approved model/API list and routing rules.
Approvals: Writes, payments, PII access require human sign-off.
Logging: Structured logs, transcripts, and replay.
Implementation plan (30 days)
- Draft policy + refusal rules; align owners.
- Set access scopes and service accounts.
- Add logging hooks + alerting; enable replay.
- Pilot one workflow in shadow then supervised mode.
- Train operators; iterate approvals by risk tier.
Controls we set by default
- Least-privilege credentials and per-environment keys.
- Redaction of PII before model calls; region routing if needed.
- Refusal rules for finance, HR, and irreversible actions.
- Alerting on errors, refusals, cost spikes, and drift.
Governance isn’t paperwork. It’s the safety net that lets you ship AI faster with confidence.
FAQ
Do we need a committee?
No. Small teams need a single owner with clear approvals, not bureaucracy.
Can we use multiple vendors?
Yes. Keep an approved list, version prompts/evals, and route by risk and cost.
How do we audit actions?
Log every call with inputs/outputs, user, tool invoked, and outcome.
What about on-prem data?
Use local models or private cloud; enforce data residency in routing rules.