As AI technologies rapidly integrate into enterprise environments, there is a critical need for enhanced visibility and governance over AI models and their supply chains. Recent studies reveal that only 6% of organizations have an advanced AI security strategy, leaving many vulnerable to sophisticated threats like shadow AI and prompt injection attacks. The lack of transparency around where and how large language models (LLMs) are used means incident response can be slow and ineffective. Current mandates for Software Bill of Materials (SBOMs) don’t fully address AI model risks, since models continuously evolve and can execute code during loading. Emerging tools like ML-BOMs and alternative model formats such as SafeTensors can improve security but require organizational commitment. To build AI supply chain visibility, organizations should start by inventorying models, managing shadow AI usage, requiring human approvals, and incorporating AI governance into vendor contracts. With regulatory requirements tightening and cyber insurance adapting, the urgency for robust AI supply chain governance has never been higher. Proactive preparation today will prevent costly breaches tomorrow.
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