Artificial intelligence has moved from the fringes of research labs into everyday conversation. Since late 2022, tools like ChatGPT have captured the world’s attention by making advanced AI capabilities accessible to anyone, not just technical experts. This rapid adoption has brought excitement and opportunity, but it has also created urgency around ethics, governance, and accountability.
Why Standards Matter
Alongside emerging regulations, international standards are proving vital in ensuring that AI systems deliver value without compromising safety or trust. Standards provide the frameworks, definitions, and processes that allow organisations to adopt AI responsibly while reducing risk. They also promote global interoperability, which is critical as AI applications cross borders and industries.
The Role of ISO and IEC
Well before AI became a mainstream topic, the International Organization for Standardization (ISO) and the International Electrotechnical Commission (IEC) recognized its potential. In 2017, they created a dedicated subcommittee, SC42, to establish foundational standards for AI and related technologies.
Their early focus was on big data, producing a five-part technical series that laid the groundwork for building large-scale models. Over time, this evolved into more specialized standards such as ISO/IEC 5392:2024, which defined a reference architecture for knowledge engineering in AI.
Key Technical Standards
Several baseline standards have since been developed to provide clarity and consistency:
- ISO/IEC 22989:2022 – establishes key terminology and concepts in AI.
- ISO/IEC 23053:2022 – outlines a framework for describing AI and machine learning systems.
These documents ensure that developers, regulators, and businesses speak the same language when working with AI technologies.
Governance and Risk Management
Technical definitions alone are not enough. To build confidence in AI, governance and risk management must be embedded at every stage. SC42 has published a series of standards addressing issues such as bias, trustworthiness, robustness of neural networks, and risk assessment methodologies.
Highlights include:
- ISO/IEC TR 24027:2021 – addressing bias in AI systems.
- ISO/IEC TR 24028:2020 – overview of trustworthiness in AI.
- ISO/IEC 23894:2022 – guidance on AI risk management.
- ISO/IEC 25059:2023 – covering quality requirements for AI systems from design through deployment.
These frameworks help organisations identify potential risks early and establish safeguards to protect users and stakeholders.
A Comprehensive Management Standard
The most significant step forward came in 2023 with the release of ISO/IEC 42001, the first international management system standard dedicated to AI. This framework sets requirements for creating, maintaining, and continually improving an Artificial Intelligence Management System (AIMS).
Aligned with other well-known ISO standards for quality, security, and privacy, ISO/IEC 42001 provides a structured approach to embedding AI governance into business operations. It ensures that AI deployments remain safe, reliable, and accountable while supporting innovation and efficiency.
Looking Ahead
The combination of regulation and global standards is shaping a future where AI can be trusted as both a business tool and a societal asset. By adopting internationally recognized best practices, organisations can deploy AI with confidence, knowing they are aligning with principles of safety, transparency, and interoperability.
As AI becomes more deeply integrated into our daily lives, these standards will be essential for building systems that not only advance technology but also strengthen trust, productivity, and long-term sustainability.
