What is AI Bill of Materials (AIBOM)?

AI systems rarely operate as standalone applications. Most rely on multiple models, datasets, APIs, plugins, open-source libraries, and cloud services working together behind the scenes. An AI Bill of Materials (AIBOM) is a structured record of those components. It helps organizations document what an AI system contains, where its dependencies come from, and how those components interact across the AI lifecycle.

In simple terms, an AIBOM acts as an ingredient list for AI systems.

Why do organizations need an AI Bill of Materials?

Organizations are increasingly adopting AI technologies across enterprise environments. However, visibility into AI dependencies and integrations can remain limited.

For example, a generative AI application may depend on:

• A third-party foundation model
• Open-source machine learning libraries
• External APIs
• Proprietary datasets
• Cloud GPU infrastructure
• Fine-tuned internal models

Without proper documentation, security and compliance teams may struggle to understand how these systems operate or where potential risks exist.

As a result, organizations are exploring AI Bill of Materials frameworks to improve governance, supply chain visibility, and risk management.

What does an AI Bill of Materials include?

An AI Bill of Materials extends traditional Software Bill of Materials (SBOM) concepts by documenting AI-specific components, workflows, and dependencies.

A typical AIBOM may include:

Security risks linked to AI supply chains

AI ecosystems can introduce additional software supply chain, governance, and dependency management risks. Many organizations now rely on external AI services, publicly available models, and rapidly changing open-source tooling.

This creates several security challenges:

Because of this, organizations need stronger visibility into how AI systems are built and maintained.

How does AIBOM supports AI governance?

An AI Bill of Materials helps organizations improve transparency across the AI supply chain. It also supports broader governance and compliance initiatives.

With an AIBOM, teams can:

• Track AI system dependencies
• Review third-party AI integrations
• Assess software and model provenance
• Support regulatory documentation efforts
• Improve incident response investigations
• Strengthen internal AI governance programs

Over time, AIBOM practices may play a larger role in AI governance and supply chain transparency, like how SBOMs support software security and dependency management.

How Hexnode help organizations maintain endpoint visibility?

Hexnode helps IT teams manage enrolled endpoints through compliance policies, app management, device details, and application inventory capabilities.

Administrators can view applications on enrolled devices and use blocklist or allowlist controls to restrict app access or limit which applications can run on supported platforms.

With Microsoft Entra Conditional Access integration, Hexnode can share device compliance status, so access policies can be enforced based on compliant devices.