"We need an AI policy" often means "we need a 40-page PDF nobody will read." SMBs need something smaller — five decisions everyone understands.
Governance isn't bureaucracy for its own sake. It's how you capture the benefits of AI without shadow tools, data leaks, or a trust crisis after one bad client email. I've helped organizations from 15 to 500 people adopt a minimal framework in days, not months.
At a glance
- Five pillars: tools, data, roles, review, escalation
- Align with existing security and privacy habits — not a parallel universe
- Quebec: connect to Law 25 and data safety basics
- Review quarterly; update when tools or use cases change
Pillar 1 — Approved tools
| Do | Don't |
|---|---|
| Maintain a short list of vetted AI tools with enterprise terms | Let every employee pick free consumer apps |
| Document why each tool is approved (data handling, region) | Assume "Microsoft/Google = automatically safe" without config |
| Block or discourage unapproved uploads of client data | Ignore shadow IT because "they're being productive" |
One page: tool name, approved use, data classes allowed, owner.
Pillar 2 — Data classification
Reuse a simple traffic light — same idea as data safety with AI:
- Green — internal drafts, non-sensitive summaries
- Yellow — personal information, contracts, financial detail — strict rules
- Red — no AI without legal/security review
Every pilot proposal should state its class before testing.
Pillar 3 — Roles and accountability
Name real people, not committees:
- Executive sponsor — sets tone, removes blockers
- Pilot owner — day-to-day, metrics, training
- IT or security liaison — access, logging, vendor review
- Users — follow rules, report issues without blame
Ambiguity here is how "the AI sent it" becomes nobody's fault.
Pillar 4 — Human review
Define what always requires human approval before external use:
- Client emails and deliverables
- Quotes, pricing, legal language
- Anything derived from yellow/red data
Internal drafts can be lighter — but human-in-the-loop isn't optional for trust.
Pillar 5 — Escalation
When something goes wrong — wrong recipient, leaked snippet, hallucinated fact in a report:
- Stop the workflow
- Notify sponsor + security
- Document incident (what, when, which tool)
- Fix process before blaming individuals
A no-blame escalation path beats a hidden workaround culture.
What the one-page policy contains
- Purpose — AI to assist, not replace accountability
- Approved tools + data classes
- Review rules
- Training link (30 min awareness)
- Contact for questions
- Review date
That's enough for most SMBs to start progressive adoption.
Governance enables speed (counterintuitively)
Teams without rules move fast individually — and stall organizationally after one incident. Clear guardrails let pilots expand because leadership isn't guessing what's happening in Slack.
Red flags you're under-governed
- "We use ChatGPT" with no enterprise agreement
- No list of what's allowed in prompts
- Client deliverables sent without second pair of eyes
- IT learns about AI usage from an invoice, not a plan
Bottom line
AI governance for SMBs isn't a legal novel. It's five decisions, written down, owned by named people, aligned with how you already treat data and client trust.
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Need a minimal governance pass before your first pilot scales? Let's talk — often one working session is enough.