AI Software & Industrial Solutions

Core Standards

• ISO/IEC 42001 - Services Management

  Information technology — Artificial intelligence — Management system

  This document specifies the requirements and provides guidance for establishing, implementing, maintaining and continually improving an AI (artificial intelligence) management system within the context of an organization.

  This document is intended for use by an organization providing or using products or services that utilize AI systems. This document is intended to help the organization develop, provide or use AI systems responsibly in pursuing its objectives and meet applicable requirements, obligations related to interested parties and expectations from them.

  This document is applicable to any organization, regardless of size, type and nature, that provides or uses products or services that utilize AI systems.

• ISO/IEC TR 5469 - Information Technology

  Artificial intelligence — Functional safety and AI systems

  This document describes the properties, related risk factors, available methods and processes relating to:

  —     use of AI inside a safety related function to realize the functionality;

  —     use of non-AI safety related functions to ensure safety for an AI controlled equipment;

  —     use of AI systems to design and develop safety related functions.

• ISO 9000 - Services Management

  Quality management systems — Fundamentals and vocabulary

  ISO 9000:2015 describes the fundamental concepts and principles of quality management which are universally applicable to the following:

  • organizations seeking sustained success through the implementation of a quality management system;
  • customers seeking confidence in an organization's ability to consistently provide products and services conforming to their requirements;
  • organizations seeking confidence in their supply chain that their product and service requirements will be met;
  • organizations and interested parties seeking to improve communication through a common understanding of the vocabulary used in quality management;
  • organizations performing conformity assessments against the requirements of ISO 9001;
  • providers of training, assessment or advice in quality management;
  • developers of related standards.

  ISO 9000:2015 specifies the terms and definitions that apply to all quality management and quality management system standards developed by ISO/TC 176.

• ISO/IEC 23894 - Information Technology

  Information technology — Artificial intelligence — Guidance on risk management

  This document provides guidance on how organizations that develop, produce, deploy or use products, systems and services that utilize artificial intelligence (AI) can manage risk specifically related to AI. The guidance also aims to assist organizations to integrate risk management into their AI-related activities and functions. It moreover describes processes for the effective implementation and integration of AI risk management.

  The application of this guidance can be customized to any organization and its context.

• ISO/TR 11065 - Manufacturing

  Industrial automation glossary

  Defines more than 550 terms relevant to automation in an industrial manufacturing environment. All the terms and definitions have been obtained from the previous approved ISO publications listed in each case as the source.

• ISO/IEC 42005 - Information Technology

  Information technology — Artificial intelligence (AI) — AI system impact assessment

  This document provides guidance for organizations performing artificial intelligence (AI) system impact assessments for individuals and societies that can be affected by an AI system and its foreseeable applications. It includes considerations for how and when to perform such assessments and at what stages of the AI system life cycle, as well as guidance for AI system impact assessment documentation.

  Additionally, this guidance includes how this AI system impact assessment process can be integrated into an organization’s AI risk management and AI management system.

  This document is intended for use by organizations developing, providing or using AI systems. This document is applicable to any organization, regardless of size, type and nature.

• ISO/IEC 27001 - Information Technology

  Information security, cybersecurity and privacy protection — Information security management systems — Requirements

  This document specifies the requirements for establishing, implementing, maintaining and continually improving an information security management system within the context of the organization. This document also includes requirements for the assessment and treatment of information security risks tailored to the needs of the organization. The requirements set out in this document are generic and are intended to be applicable to all organizations, regardless of type, size or nature.

• ISO/IEC 5259-5 - Information Technology

  Artificial intelligence — Data quality for analytics and machine learning (ML) — Part 5: Data quality governance framework

  This document provides a data quality governance framework for analytics and machine learning (ML) to enable governing bodies of organizations to direct and oversee the implementation and operation of data quality measures, management, and related processes with adequate controls throughout the data life cycle (DLC) model according to ISO/IEC 5259-1.

  This document can be applied to any analytics and ML. This document does not define specific management requirements or process requirements according to ISO/IEC 5259-3 and ISO/IEC 5259-4 respectively.

• ISO/IEC 27034-3 - Information Technology

  Information technology — Application security — Part 3: Application security management process

  This document provides a detailed description and implementation guidance for the Application Security Management Process.

• ISO/IEC 23053 - Information Technology

  Framework for Artificial Intelligence (AI) Systems Using Machine Learning (ML)

  This document establishes an Artificial Intelligence (AI) and Machine Learning (ML) framework for describing a generic AI system using ML technology. The framework describes the system components and their functions in the AI ecosystem. This document is applicable to all types and sizes of organizations, including public and private companies, government entities, and not-for-profit organizations, that are implementing or using AI systems.