ISO/IEC TR 27563:2023 provides guidance on security and privacy in artificial intelligence use cases, with a focus on best practices that can support technical review, documented evaluation, and compliance workflows. As a technical report linked to the broader ISO/IEC TR 27563 series, it is relevant for teams assessing how AI-enabled systems handle sensitive data, control access, and manage operational risk. It can also help procurement, engineering, and assurance teams align internal review criteria with practical security and privacy expectations.

What is ISO/IEC TR 27563:2023?

ISO/IEC TR 27563:2023 is a supporting technical reference on security and privacy in artificial intelligence use cases - Best practices. Its purpose is generally to help organizations frame technical assessment activities around AI deployments where data protection, access control, and risk management are important. Because it is a derived document connected to ISO/IEC TR 27563, it is best understood as guidance that can inform engineering documentation, conformity assessment preparation, and internal governance rather than as a standalone product specification.

Applications of ISO/IEC TR 27563:2023

Organizations may use ISO/IEC TR 27563:2023 when reviewing AI systems that process personal, operational, or otherwise sensitive information. It is relevant to security teams, privacy officers, solution architects, laboratories, and compliance functions that need a structured reference for technical validation and operational consistency. Typical use cases can include vendor evaluation, internal control design, documented evaluation of AI features, and review of safeguards in environments where data handling and system behavior must be justified during regulatory preparation or assurance activities.

Why is ISO/IEC TR 27563:2023 important?

Security and privacy expectations are often central to AI deployment decisions, especially where organizations need to demonstrate due diligence and reduce implementation risk. ISO/IEC TR 27563:2023 can support testing workflows, quality assurance, and conformity assessment preparation by giving teams a common reference point for best practices. It may also improve consistency across procurement, engineering documentation, and technical review processes, helping organizations compare solutions more effectively and maintain a clearer compliance posture during product evaluation and operational change management.

• Best-practice guidance for security and privacy considerations in AI use cases
• Useful for technical review, documented evaluation, and internal control alignment
• Supports compliance workflows, procurement checks, and risk management planning
• Helps structure assessment criteria for AI-related governance and assurance activities