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Enterprises in the AI Supply Chain: Roles Explained

This episode of the ISACA Advanced in AI Security Management (AAISM) exam prep series looks at why every enterprise depends on third parties, the risks those relationships introduce, and the crucial distinction between being an AI provider and an AI deployer. Your responsibilities and your legal liability depend heavily on which role you play in the AI supply chain, so knowing the difference lets you understand exactly what you are accountable for, what you can expect from your vendors, and where the lines of responsibility actually fall.

What this episode covers

Watch the full episode above for the worked examples and detailed explanations of each concept.

Frequently Asked Questions

What is the difference between an AI provider and an AI deployer?

A provider is the entity that supplies the AI solution, while a deployer is the entity that uses it. Their duties differ sharply: under the European Union’s AI Act, the provider carries the heavier compliance load while the deployer is responsible for proper use, oversight, and transparency.

What third-party risks affect the AI supply chain?

Third-party relationships carry operational risk like production delays, financial risk like a supplier going bankrupt, cybersecurity risk like a partner’s data breach, compliance and ethics risk, geopolitical risk from sanctions or conflict, environmental risk from natural disasters, and reputational risk when a supplier behaves badly. AI does not remove these; it adds new vendors and reshapes existing relationships.

What duties do AI providers have under the EU AI Act?

Under the European Union’s AI Act, the provider ensures high-risk systems meet legal requirements, runs conformity assessments, maintains technical documentation, monitors performance, and reports serious incidents to authorities. This heavier compliance burden reflects the provider’s role in designing and building the system.

Who are the AI actors described by the NIST framework?

The NIST framework describes a whole cast of AI actors across the life cycle: designers, data scientists, and domain experts at the design stage, developers and integrators in build, operators, evaluators, and auditors in use, and the governance leaders and boards who provide oversight. Responsibility is shared across many hands.

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Reference: This article is based on concepts discussed in Enterprises in the AI Supply Chain: Roles Explained.