The AI bill of materials (AIBOM)

By Sam Rivera, Founder, SentinelPanda · June 19, 2026 · 1 min read · AI Governance

You cannot govern or secure an AI system whose ingredients you cannot list. The AIBOM is the ingredient label for AI — models, data, and dependencies.

From SBOM to AIBOM

Software supply-chain security gave us the software bill of materials (SBOM) — a list of the components in a piece of software. AI systems have additional ingredients an SBOM does not capture: the models, the datasets, the pre-trained weights, and the ML libraries. The AI bill of materials extends the idea to cover them.

What it captures

• Models used (built, fine-tuned, or third-party) and their versions and sources.
• Datasets used for training and evaluation, with provenance and licensing.
• ML frameworks and dependencies, and the relationships between components.

Why it is emerging

As AI supply chains grow — a fine-tune of an open model trained on mixed datasets, served via a vendor API — the questions of "what is actually in this system, where did it come from, and are we allowed to use it" get hard to answer without a record. The AIBOM is that record, supporting security, licensing, and governance documentation.

Practical use

You do not need a heavyweight standard to start — capture, per AI system, its models, data sources, and key dependencies with provenance. That feeds vulnerability response (a flawed model or dataset), licensing checks, and the technical documentation frameworks require. SentinelPanda links these components to each AI system in the inventory.