Google Vertex AI
Compliance Guide
Google Cloud offers some of the most advanced AI monitoring tools. We show you how to leverage Vertex AI's native features to satisfy the rigorous requirements of ISO 42001.
GCP Control Mapping
VPC Service Controls
Create a security perimeter to mitigate data exfiltration risks from Vertex AI.
Vertex AI Model Monitoring
Detect feature attribution drift and prediction drift in production models.
Cloud IAM & Service Accounts
Fine-grained permissions for model deployment and dataset access.
Dataplex & Cloud Data Loss Prevention
Scan and redact PII from training datasets before they reach the model.
Explainability & Transparency
The EU AI Act places a heavy emphasis on "Explainability" for high-risk systems. Vertex AI's "Explainable AI" feature is a core component of your compliance strategy.
Feature Attribution
Understand which features contributed most to a specific AI prediction for audit logs.
Human Oversight
Using Google Cloud's "Human-in-the-Loop" workflows for model validation.
Implementing AI Governance on GCP
Need help configuring your Google Cloud environment for ISO 42001?
Back to HubKevin A
Principal Security & GRC Engineer
Kevin is a security engineer turned GRC specialist. He focuses on mapping cloud-native infrastructure (AWS/Azure/GCP) to modern compliance frameworks, ensuring that security controls are both robust and auditor-ready without slowing down development cycles.