Skip to main content
52 days

Super Intelligence definition proposal due (60 days) · Nov 28, 2026 · See what changes

Risk Assessment

AI Risk Assessment for Small Teams

Most small teams skip risk assessment because it sounds like enterprise compliance overhead. It doesn't have to be. Here's a practical, lightweight approach to identifying and managing AI risks before they become incidents.

Related guides

Frequently Asked Questions

How often should we run an AI risk assessment?
At minimum: when adopting a new AI tool, when a tool's scope changes significantly, and once a year as a general review. For fast-moving tools, quarterly is better.
What are the biggest AI risks for small teams?
Data leakage (employees sharing sensitive data with LLMs), shadow AI (unapproved tools), vendor lock-in, and hallucination-driven mistakes in customer-facing work.
Do we need a dedicated risk officer?
No. A single owner — often an ops lead, CTO, or founder — can run a lightweight risk process for most small teams. The key is documenting decisions, not creating bureaucracy.
What's the difference between AI risk and regular software risk?
AI systems are non-deterministic — the same input can produce different outputs. This makes testing harder and means you need ongoing monitoring, not just pre-launch QA.