ISO/IEC TR 24028:2020 provides a technical overview of trustworthiness in artificial intelligence, helping organizations understand the factors that influence confidence in AI-enabled systems. As a derived document connected to ISO/IEC TR 24028, it is useful for teams assessing AI-related risk management, technical review, and compliance workflows. For engineering, procurement, and governance teams, ISO/IEC TR 24028:2020 can support documented evaluation of AI capabilities, limitations, and expected operational behavior during product evaluation and regulatory preparation.

ISO/IEC TR 24028:2020 standard overview

ISO/IEC TR 24028:2020 focuses on the overview of trustworthiness in artificial intelligence, which typically includes the considerations organizations use to judge whether AI systems are dependable for intended use. In practice, that may involve technical assessment of reliability, transparency, robustness, and associated risk factors. As a supporting reference tied to the parent document, it is relevant where teams need a structured compliance reference for engineering documentation, verification activities, and quality workflows surrounding AI-enabled products and services.

Applications of ISO/IEC TR 24028:2020

ISO/IEC TR 24028:2020 is commonly used in AI system development, model review, and conformity assessment preparation where trustworthiness needs to be documented and evaluated. It may support internal engineering validation, supplier due diligence, laboratory evaluation, and technical review of AI features embedded in software, control systems, or automated decision workflows. Organizations may also use it when aligning documentation across development, testing, procurement, and governance processes for operational consistency and risk reduction.

Why ISO/IEC TR 24028:2020 matters

This technical document matters because trustworthiness is often central to safe and defensible AI deployment. ISO/IEC TR 24028:2020 can help teams define the evidence needed for compliance workflows, testing consistency, and conformity assessment preparation. It is especially useful where engineering groups need to compare expected behavior against documented requirements, support technical validation, and reduce implementation risk. For organizations buying or integrating AI-based solutions, it can also inform procurement review and quality assurance decisions.

• Overview of trustworthiness considerations for AI systems and related technical documentation
• Useful for risk management, verification activities, and technical assessment workflows
• Supports engineering documentation, procurement review, and conformity assessment preparation
• Relevant where AI reliability, robustness, and operational consistency must be evaluated