ISO/IEC 24668:2022 addresses process management for big data analytics within artificial intelligence work, making it relevant for teams that need a structured technical reference for planning, governing, and reviewing analytics-related activities. As a compliance reference, it can support documented evaluation, technical assessment, and operational consistency across data-driven projects. ISO/IEC 24668:2022 is especially useful where organizations need clearer process control around AI-enabled analytics, procurement review, and internal quality workflows tied to data handling and validation.

Purpose of ISO/IEC 24668:2022

The purpose of ISO/IEC 24668:2022 is generally to provide a framework for managing processes used in big data analytics for artificial intelligence applications. Based on its title, it is likely intended to help organizations define, organize, and review the process side of analytics work rather than the analytics outputs alone. That makes it relevant for engineering documentation, technical review, and conformity assessment preparation where controlled methods, traceability, and repeatable workflows are important.

Compliance applications of ISO/IEC 24668:2022

In compliance workflows, ISO/IEC 24668:2022 may be used to align internal procedures for AI-related analytics projects with documented process expectations. It can support procurement teams evaluating technical documents, laboratories or validation teams reviewing analysis methods, and compliance groups preparing evidence for regulatory preparation or audit readiness. Organizations working with data platforms, software systems, or AI-enabled decision support tools may use it to improve technical validation, review checkpoints, and consistency across project lifecycles.

Benefits of ISO/IEC 24668:2022

Using ISO/IEC 24668:2022 can improve control over big data analytics processes by supporting clearer responsibilities, more consistent verification activities, and stronger quality assurance. For organizations, that often translates into better risk management, more reliable technical documentation, and easier preparation for conformity assessment. It may also help reduce variation between projects, support procurement decisions, and provide a more structured basis for reviewing performance criteria, testing workflows, and operational consistency in AI-related analytics programs.

• Framework support for managing big data analytics processes in AI-related work
• Useful for technical assessment, documented evaluation, and internal review workflows
• Helps align engineering documentation with compliance and quality objectives
• Relevant to procurement, audit preparation, and conformity assessment activities