Defining AI Bill of Materials: Structure, Scope, and Role in AI Trust Services

This IDC Perspective examines the emergence of the AI bill of materials (AI BOM) as a foundational framework to manage the growing complexity of AI systems. As enterprises transition toward agentic, distributed, and continuously evolving AI architectures, traditional governance and security models are proving insufficient. The document outlines the structure, scope, and operationalization of AI BOM, highlighting its role in enabling system-level visibility, traceability, and control across models, data, pipelines, and runtime environments. It also explores enterprise adoption drivers, regulatory influences, and vendor approaches, positioning AI BOM as a critical control layer for managing risk, cost, and compliance in modern AI ecosystems."AI systems are evolving into distributed, stateful execution environments composed of models, data pipelines, prompt orchestration layers, APIs, and autonomous agents operating across dynamic runtime contexts. AI BOM functions as the control plane for this architecture, capturing dependency graphs, lineage, identity propagation, and runtime telemetry in a machine-readable form. Without this, enterprises cannot correlate system behavior with underlying components, resulting in blind spots across governance, security, and operational integrity as AI systems scale," says Sakshi Grover, senior research manager, Cybersecurity Products and Services, IDC..