This guide explains how a smaller organization can use a simple risk register to ask better questions before and during the use of AI. It is general guidance, not a verified framework mapping, certification claim, compliance determination, or substitute for context-specific professional advice.

A Useful Starting Structure

Start by reviewing AI risks across eight practical categories:

• Bias and Fairness
• Security and Privacy
• Transparency and Explainability
• Data Quality and Integrity
• Regulatory Compliance
• Operational Risks
• Human Impact and Safety
• Third-Party and Vendor

Getting Started

Start with the systems and decisions that matter most to your organization. Record the risk, who owns it, the controls already in place, what evidence supports the rating, and when it should be reviewed. Use context-specific legal, privacy, security, safety, and risk advice where the consequences warrant it.

Key Takeaways

• AI risk management doesn't have to be complicated
• Start with identifying your top 5-10 highest-priority risks
• Document mitigation strategies that fit your organization
• Review after material changes or incidents and on a schedule justified by the actual risk

Keep the register small enough to maintain, clear enough for another person to understand, and tied to evidence rather than optimistic assumptions.