AI policy and acceptable use
A governance policy and a staff acceptable-use standard, fitted to your position and reviewed by your counsel.
Governance & Operations
AI Governance Starter
Policies, templates, and workflows to govern how your organization uses AI.
Download the PDFWhat you get
Documented answers when a regulator, customer, or board asks how you govern AI.
Get the AI Governance Starter overview
The problem it solves, what is included, how it works, the technical components, and how we adapt it with you.
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The problem
The board asks how you govern AI. The answer is scattered.
AI is already in use: vendor features, pilots, models, and agents. Policies are drafts, the inventory is a spreadsheet nobody updates, and every customer security questionnaire starts from scratch.
What this accelerator does
The AI Governance Starter gives you working governance records on day one, a risk tier for every system, and a check that fails when records fall out of date.
What's included
Governance records that stay current.
Four parts, each adapted to your data, platforms, and controls.
Risk assessment and inventory
A questionnaire with scoring and controls per tier, and an inventory of models, vendor AI features, and agents.
Evaluation Cards and Control Register
A card per live system and a register of 18 starting controls with owners and evidence.
Evidence packs
Generated on request for auditors, customer security questionnaires, and board reports.
You keep the policies, the records, and the check, in plain CSV, YAML, and Markdown that open in Excel and import into a GRC tool later.
How it works
Setting it up.
Records folder
Inventory, control register, assessments, and cards in your repository, reviewed like code.
Adapt the policies
Roles, approved tools, and prohibited uses to match your position and the law where you operate.
Tune the questionnaire
Scores, thresholds, and controls per tier, approved by your AI governance committee.
Fill the register
An owner, enforcement method, evidence, and honest status for each control.
Register what exists
Every AI system in use today, assessed, with its gaps listed.
Check in CI
Any change that leaves a production system without a current review, card, or control fails.
Technical detail
What the check looks for.
Vendor-neutral Python and configuration, Azure first, with tests included from the start.
- Inventory
- Required fields, different owner and backup, reviews not overdue
- Risk assessments
- One per system past intake; inventory tier not lower than assessed
- Evaluation Cards
- Present and current for every live system
- Agents
- A scope file that matches the inventory's agent and owner
- Control register
- Owners and evidence for controls in place; tests not overdue
- Coverage
- Every control a live system's tier requires is in place
Proof in the package
Worked example: three AI systems, fully documented.
A demand forecast model, a support-answers assistant, and an invoice-triage agent, each assessed and carded.
One command builds an evidence pack from
- The AI inventory and each system's risk tier
- Risk assessments and Evaluation Cards
- The Control Register, with owners and evidence
- Test results and audit logs from the other accelerators
Result
The pack can cover every system, or only the ones a given customer uses. A coverage gap on a production system fails the check.
Where it fits
Platforms, related accelerators, and limits.
Works with
- Your version control and existing CI
- Excel for the CSV records
- GRC tools through CSV import
Pairs with
- AI Agent Controls enforce controls AIG-06, 07, 08, and 10
- MLOps Templates write Evaluation Cards
- Evaluation results and agent audit logs serve as evidence
Assumptions and limits
- Policies are starting drafts, not legal advice; your counsel reviews them
- The NIST AI RMF and ISO/IEC 42001 crosswalk is informal; your auditor checks it
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