Your AI Supply Chain Has a Blind Spot. Read the New Gartner® Report to Find Out Where it is.
Your SBOM tools can tell you every library in your codebase. What they can't tell you is what's inside the model you pulled from a public repository, what data trained it, or what your agent just did when it called a plugin or an MCP server five minutes ago.
That second part doesn't sit still the way a codebase does. A model or a dataset is at least a fixed artifact, something you can hash, version, and put in a registry. An agent makes a new decision every time it runs, and it can reach for a tool or server nobody reviewed in advance. The new Gartner report, 5 Steps to Secure Your AI Supply Chain, names both halves of this gap directly – static artifacts and live agentic behavior – and lays out what closing each one actually requires.
Download the Gartner Report
What you'll learn
Why traditional SBOM and SCA tools are structurally blind to model weights, training datasets, and the agentic tool calls and MCP connections that extend your environment at runtime
Why agents introduce a separate, ongoing category of risk that no inventory can fully capture: what an agent is authorized to do, and what it actually does once it's live
A five-step maturity path: solidify the foundation, implement an AIBOM, verify model and data integrity, manage behavioral risk for agentic AI, and mobilize end-to-end defense
Where purpose-built tooling fits into closing this gap, including Noma's role in it
Why Noma is a market shaper
Noma covers the full spectrum in one platform. We discover every agent, govern what each one can access and do, and watch its behavior at runtime, stopping the risky action before it happens.