AI Risk Assessment for Your Stack
Assessing risk across your AI tools helps you prioritize mitigation and avoid surprises. This guide covers risk categories, a simple risk matrix template, and mitigation strategies for each risk type. Practical and template-driven.
Risk Categories
Data leakage — Sensitive data sent to AI tools. Training use, breaches, or unauthorized access. Mitigation: data controls, DPAs, opt-out, encryption.
Bias — AI outputs that discriminate or disadvantage groups. Hiring, lending, support. Mitigation: audit, human review, diverse data, vendor selection.
Misinformation — Hallucinations, wrong facts, or misleading content. Customer-facing or internal. Mitigation: verification, RAG, grounding, human review.
Compliance violation — Breach of GDPR, EU AI Act, sector rules. Fines and enforcement. Mitigation: map obligations, vendor review, documentation.
Dependency risk — Over-reliance on a vendor. Lock-in, outage, or discontinuation. Mitigation: diversification, export, backup plans.
Simple Risk Matrix
| Risk | Likelihood (1-5) | Impact (1-5) | Score (L×I) | Priority |
|---|---|---|---|---|
| Data leakage | ||||
| Bias | ||||
| Misinformation | ||||
| Compliance | ||||
| Dependency |
Likelihood — 1 = rare, 5 = likely. Impact — 1 = low, 5 = severe. Score — Multiply. Higher = higher priority. Priority — Address high scores first.
Mitigation Strategies
Data leakage — Use tools with no training on your data. DPAs. Encrypt. Minimize data sent. Audit what vendors receive.
Bias — Audit outputs for fairness. Human review for high-stakes decisions. Diversify training data where you control it. Choose vendors with bias audits.
Misinformation — Verify facts. Use RAG for grounded answers. Lower temperature for factual tasks. Human review before publication. Do not use AI for unverified claims.
Compliance — Map regulations (EU AI Act, GDPR, sector). Vendor compliance. Document decisions. Train staff. Legal review for high-risk use.
Dependency — Avoid single-vendor lock-in. Export data. Have backup tools or processes. Monitor vendor health and roadmap.
Template: Per-Tool Assessment
For each tool:
- Tool — Name
- Data — What data does it receive? Sensitive?
- Use case — What do you use it for? Customer-facing?
- Risks — Data leakage, bias, misinformation, compliance, dependency
- Mitigation — What you do to reduce each risk
- Owner — Who is responsible
Update quarterly or when use changes.
The Bottom Line
Assess risk across your AI stack. Use the matrix to prioritize. Mitigate each category with specific actions. Document and review. Risk assessment is ongoing, not one-time.