AI Vendor Risk Management: Managing Third-Party AI Risks Under the EU AI Act

Businesses increasingly depend on third-party AI models, APIs and software to develop products and automate operations. While these tools offer efficiency, they also introduce risks related to data privacy, security, technical documentation and regulatory responsibilities.

The EU AI Act (Regulation (EU) 2024/1689) makes it important for organisations to understand how they develop, integrate and use AI systems. Working with an external AI vendor does not automatically transfer all regulatory responsibilities to that supplier.

Why AI Vendor Risk Management Matters

AI suppliers may provide models, cloud services, APIs or complete AI applications. Organisations need visibility into how these technologies work, what data they process and which parties are responsible for different activities.

A structured AI third-party risk management process helps businesses identify AI dependencies, assess supplier risks and maintain appropriate governance records.

Key EU AI Act Considerations

The organisation's role matters. A company developing and placing an AI system on the market under its own name may be a provider, while a business using an AI system under its authority for professional activities may be a deployer.

Article 25(4) addresses certain relationships between providers of high-risk AI systems and third parties supplying components, services or processes used in those systems. Where applicable, written agreements must address the information, technical access and assistance needed to fulfil regulatory obligations.

Article 53 also establishes documentation requirements for providers of general-purpose AI models, including information made available to downstream providers integrating those models into their own AI systems.

How to Assess an AI Vendor

An effective AI vendor risk assessment should include:

• Vendor identification: Record the supplier, AI system, business purpose and internal owner.

• Regulatory role assessment: Determine whether the organisation acts as a provider or deployer.

• Technical documentation: Review model capabilities, limitations, instructions and integration information.

• Data protection: Understand data processing, storage, security measures and subprocessors.

• Contractual safeguards: Define responsibilities, documentation access and incident communication.

• Ongoing monitoring: Reassess suppliers when models, services or processing arrangements change.

ISO/IEC 42001 and ISO/IEC 27001 can also support structured AI and information security supplier management. However, certification alone does not establish compliance with the EU AI Act.

Supporting AI Governance with Compliance Software

Managing supplier assessments, AI inventories, regulatory obligations and technical evidence across separate tools can make oversight difficult.

AI compliance software can help organisations centralise these activities. AnnexOps AI compliance software supports AI system inventory, risk classification, obligation mapping, documentation and evidence management.

For organisations building a structured governance process, the EU AI Act compliance lifecycle provides further guidance on managing compliance activities throughout an AI system's lifecycle.

Effective AI vendor risk management is an ongoing process. By combining supplier due diligence, clear responsibilities, technical documentation and continuous monitoring, businesses can improve visibility into third-party AI dependencies and strengthen their AI governance operations.