Building a Secure and Compliant Azure AI Landing Zone: Policy Framework & Best Practices

Microsoft

Oct 01, 2025

In an AI-first world, deploying models, inference endpoints, or cognitive services without governance is risky. We need guardrails — ensuring security, compliance, cost control, and responsible AI. In this post, we’ll explore how to build a Policy & Compliance Framework specifically for Azure AI Landing Zone (AI ALZ), and how to implement it at scale using Enterprise Policy as Code (EPAC).

As organizations accelerate their AI adoption on Microsoft Azure, governance, compliance, and security become critical pillars for success. Deploying AI workloads without a structured compliance framework can expose enterprises to data privacy issues, misconfigurations, and regulatory risks.

To address this challenge, the Azure AI Landing Zone provides a scalable and secure foundation — bringing together Azure Policy, Blueprints, and Infrastructure-as-Code (IaC) to ensure every resource aligns with organizational and regulatory standards.

The Azure Policy & Compliance Framework acts as the governance backbone of this landing zone. It enforces consistency across environments by applying policy definitions, initiatives, and assignments that monitor and remediate non-compliant resources automatically.

This blog will guide you through:

🧭 The architecture and layers of an AI Landing Zone
🧩 How Azure Policy as Code enables automated governance
⚙️ Steps to implement and deploy policies using IaC pipelines
📈 Visualizing compliance flows for AI-specific resources

What is Azure AI Landing Zone (AI ALZ)?

AI ALZ is a foundational architecture that integrates core Azure services (ML, OpenAI, Cognitive Services) with best practices in identity, networking, governance, and operations. To ensure consistency, security, and responsibility, a robust policy framework is essential.

Policy & Compliance in AI ALZ

Azure Policy helps enforce standards across subscriptions and resource groups. You define policies (single rules), group them into initiatives (policy sets), and assign them with certain scopes & exemptions. Compliance reporting helps surface noncompliant resources for mitigation.

In AI workloads, some unique considerations:

Sensitive data (PII, models)
Model accountability, logging, audit trails
Cost & performance from heavy compute usage
Preview features and frequent updates

Scope

This framework covers:

Azure Machine Learning (AML)
Azure API Management
Azure AI Foundry
Azure App Service
Azure Cognitive Services
Azure OpenAI
Azure Storage Accounts
Azure Databases (SQL, Cosmos DB, MySQL, PostgreSQL)
Azure Key Vault
Azure Kubernetes Service

Core Policy Categories

1. Networking & Access Control

Restrict resource deployment to approved regions (e.g., Europe only).
Enforce private link and private endpoint usage for all critical resources.
Disable public network access for workspaces, storage, search, and key vaults.

2. Identity & Authentication

Require user-assigned managed identities for resource access.
Disable local authentication; enforce Microsoft Entra ID (Azure AD) authentication.

3. Data Protection

Enforce encryption at rest with customer-managed keys (CMK).
Restrict public access to storage accounts and databases.

4. Monitoring & Logging

Deploy diagnostic settings to Log Analytics for all key resources.
Ensure activity/resource logs are enabled and retained for at least one year.

5. Resource-Specific Guardrails

Apply built-in and custom policy initiatives for OpenAI, Kubernetes, App Services, Databases, etc.

A detailed list of all policies is bundled and attached at the end of this blog. Be sure to check it out for a ready-to-use Excel file—perfect for customer workshops—which includes policy type (Standalone/Initiative), origin (Built-in/Custom), and more.

Implementation: Policy-as-Code using EPAC

To turn policies from Excel/JSON into operational governance, Enterprise Policy as Code (EPAC) is a powerful tool. EPAC transforms policy artifacts into a desired state repository and handles deployment, lifecycle, versioning, and CI/CD automation.

What is EPAC & Why Use It?

EPAC is a set of PowerShell scripts / modules to deploy policy definitions, initiatives, assignments, role assignments, exemptions. Enterprise Policy As Code (EPAC)
It supports CI/CD integration (GitHub Actions, Azure DevOps) so policy changes can be treated like code.
It handles ordering, dependency resolution, and enforcement of a “desired state” — any policy resources not in your repo may be pruned (depending on configuration).
It integrates with Azure Landing Zones (including governance baseline) out of the box.