AI Risk Management
for Production ML Systems
Enumerate, mitigate, and audit AI-specific risks in a single register — with owners, due dates, and automatic links to ISO 42001 and EU AI Act controls.
AI risk management is the practice of listing the harms an AI system can cause, planning mitigations, assigning owners, and tracking residual risk. Traditional risk registers do not cover the AI-specific hazards — Zilonex Govern gives you a schema and taxonomy built for machine learning.
AI-specific risks you should be tracking
A model produces systematically worse outcomes for a protected group. Mitigations: fairness scans on training data and outputs, disparate-impact thresholds, human review for edge cases.
Model performance degrades silently as production data shifts away from the training distribution. Mitigations: continuous evaluation on a held-out canary set, drift alerts, scheduled retraining.
A generative model produces confident, fluent, and wrong output. Mitigations: retrieval-augmented generation, grounded citations, refusal prompts, output filters.
An attacker embeds instructions in user input or retrieved documents that hijack the model. Mitigations: input sanitisation, prompt isolation, tool-call allow-lists, output validation.
An attacker seeds the training corpus with samples that create backdoors or degrade accuracy. Mitigations: dataset provenance, source pinning, anomaly detection during training.
A model memorises and regurgitates training data — copyrighted text, code, or personal information. Mitigations: deduplication, differential privacy, output scanning, secret detection.
What a good risk register entry looks like
- Title and description — plain-English, specific to your model
- Affected models — linked from the Zilonex Govern model registry
- Likelihood and impact — a simple 1-5 scale is enough
- Current mitigations — what already exists in code, in policy, in monitoring
- Planned mitigations — owner, due date, status
- Residual risk — the score after mitigations, with an accountable sign-off
- Linked controls — ISO 42001 clauses and EU AI Act obligations addressed
Connecting the register to ISO 42001
ISO 42001 clause 6.1 requires an AI risk assessment. Every risk in Zilonex Govern auto-links to the ISO 42001 controls it satisfies. When an auditor opens a control, they see the risks it addresses. When they open a risk, they see the controls behind it.
The same evidence pack answers EU AI Act Article 9 (risk management system) obligations for high-risk systems.
Frequently asked questions
What is AI risk management?
AI risk management is the discipline of enumerating, mitigating, and monitoring the harms an AI system can cause — to users, to the business, and to third parties. It goes beyond traditional information-security risk to include model-specific hazards like bias, drift, hallucination, prompt injection, data poisoning, and IP leakage.
How is AI risk different from cybersecurity risk?
Cybersecurity risk asks "can an attacker breach the system?". AI risk also asks "does the system misbehave even when nobody attacks it?". A model can be perfectly secure and still produce biased loan decisions, hallucinate legal citations, or drift silently as the world changes around it.
What goes in an AI risk register?
Each risk entry records: title, description, affected model(s), likelihood, impact, current mitigations, planned mitigations with owner and due date, residual risk score, and link to the ISO 42001 or EU AI Act controls it maps to. Zilonex Govern provides this schema out of the box.
How does this map to ISO 42001?
ISO 42001 clause 6.1 requires a risk-based approach. Every risk in your Zilonex Govern register auto-links to the ISO 42001 controls it addresses, so evidence flows both ways — auditors see the risks behind each control and the controls behind each risk.
Can Zilonex Govern detect drift automatically?
Zilonex Govern accepts drift metrics from your monitoring stack (Arize, Evidently, WhyLabs, custom Prometheus) and opens a risk-register entry automatically when a threshold is crossed. It is not a monitoring platform itself, but it is the governance layer on top.
Who owns AI risks?
Every risk in Zilonex Govern must have a single named owner. Unowned risks are highlighted on the dashboard. The pattern we recommend: the model owner owns the technical mitigations, a product manager owns the user-facing mitigations, and the CTO owns the residual risk sign-off.
Start your AI risk register
Owned entries, ISO 42001 links, and audit-ready export from $99/month.
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