Building an AI Governance Program: The Practical Guide for Mid-Size Companies
You don't need a team of 10 to build an effective AI governance program. This guide covers the essentials: policy, inventory, risk assessment, and documentation.
Most AI governance guides are written for Fortune 500 companies with dedicated AI ethics teams. This one is for mid-size companies (50–1,000 employees) that use AI in their products or operations and need a real program — not just a policy document that nobody reads.
What an AI Governance Program Is (and Isn't)
An AI governance program is the set of policies, processes, and controls that ensure your organization uses AI responsibly and in compliance with applicable laws.
It is not:
- A one-time audit
- A policy document filed and forgotten
- Something only your legal team handles
It is:
- An ongoing operational function
- Cross-functional (involves legal, engineering, HR, and business teams)
- Proportional to your AI risk exposure
Step 1: Build Your AI Inventory
You cannot govern what you haven't catalogued. Start by inventorying every AI system your organization uses or deploys:
For each system, document:
- What it does (description)
- Who uses it (internal / external / both)
- What decisions it influences or makes
- Who is affected (employees / customers / applicants)
- What data it uses
- Who owns it (internal team or vendor)
- Which regulations apply to it
Use a spreadsheet to start. Upgrade to a governance platform when the inventory gets complex.
Step 2: Classify Your AI Systems by Risk
Group your AI systems into risk tiers:
| Tier | Criteria | Examples |
|---|---|---|
| High | Makes consequential decisions about individuals | Hiring AI, credit scoring, healthcare diagnostics |
| Medium | Influences decisions but has human review | Customer segmentation, content recommendation |
| Low | Internal tools, limited impact | Internal search, document summarization |
High-risk systems need impact assessments, monitoring, and audit trails. Low-risk systems need basic documentation.
Step 3: Assign Ownership
Every high and medium risk AI system needs an owner — a person responsible for that system's governance compliance. This is usually the product manager or business unit head using the system.
AI owners are responsible for:
- Keeping documentation current
- Ensuring periodic reviews happen
- Escalating when the system changes materially
Step 4: Write Your AI Policy
Your AI policy should be 2–5 pages, not 50. Cover:
- Scope — what systems and decisions are covered
- Prohibited uses — what AI cannot be used for (e.g., facial recognition without consent)
- Approval process — how new AI tools get evaluated before adoption
- Vendor due diligence — what you require from AI vendors
- Consumer-facing AI — disclosure and opt-out requirements
- Incident response — how to handle an AI-related failure or harm
- Review cadence — how often the policy and AI inventory are reviewed
- Purpose: What problem does this solve?
- Inputs: What data does it use?
- Outputs: What does it produce?
- Decision: How does its output affect people?
- Bias risk: How was it tested for discriminatory outcomes?
- Human oversight: What human review exists before the decision is final?
- Mitigation: What controls reduce discrimination risk?
- Opt-out: Can affected individuals opt out?
- Drift: Is the model's accuracy declining?
- Disparate impact: Are outcomes skewed across demographic groups?
- Errors: Are there anomalous outputs?
- All staff: AI literacy basics, what AI is used for, how to report concerns
- AI users: How to use AI tools responsibly, what the outputs mean and their limits
- AI owners: Governance obligations, how to conduct reviews, escalation paths
- Leadership: Regulatory risk landscape, board-level governance
- Staff time: 0.25 FTE of a compliance/legal person ongoing + quarterly reviews from AI owners
- Technology: $0–$500/month (spreadsheet to start, governance SaaS if you have 10+ AI systems)
- External: $5K–$15K if you engage a consultant to set up the program initially
Step 5: Conduct Impact Assessments for High-Risk Systems
For each high-risk AI system, document:
Update impact assessments annually or when the system changes.
Step 6: Set Up Monitoring
High-risk AI systems need ongoing monitoring for:
Set up quarterly reviews with metrics dashboards for each high-risk system.
Step 7: Train Your Team
Train these groups differently:
EU AI Act requires AI literacy training for relevant staff — so document it.
What This Costs
A basic program for a mid-size company should cost:
Resources
Related Regulations
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Check My ComplianceNot legal advice. This article is for informational purposes only. Always consult a qualified attorney for compliance decisions.