ISO Standards for Risk Management in Artificial Intelligence
Artificial Intelligence (AI) is reshaping the foundations of the economy, governance and everyday life. From automated medical diagnoses to algorithms that define access to credit or judicial decisions, the transformative potential of AI is immense. But with that potential emerge complex risks: algorithmic biases, lack of transparency, unforeseen societal impacts, technical failures, and ethical dilemmas that challenge traditional frameworks of accountability.
Faced with this scenario, ISO international standards represent an articulated, structured and forward-looking response. They are not mere technical guidelines, but governance foundations that make it possible to build a trustworthy AI, with traceability, ethics and a focus on human rights.
Key regulatory fundamentals
ISO/IEC 23894:2023. Risk management in AI systems
It is the most specific standard of the set. It establishes guidelines for identifying, assessing and addressing the unique risks of IA systems, from design to decommissioning. It relies on a lifecycle approach, allowing risk management to be tailored to the different phases: development, training, implementation and decommissioning.
🔍 Differential value: Considers technical as well as ethical and social risks, and introduces the concept of "emerging risk", key in non-deterministic technologies.
ISO 31000:2018. Risk management for all types of organizations
It is the basis on which other more specific standards are built. It defines principles, structure and processes that enable risk management to be integrated into the organizational culture. The standard emphasizes the importance of leadership, effective communication and continuous improvement.
🔍 Differential value: Allows for the establishment of a robust risk management system that can be adapted to the complexity of AI without losing institutional coherence.
ISO Guide 73:2009. Risk management vocabulary
This guide acts as a normative dictionary. It unifies the terminology used in different risk management standards, avoiding misunderstandings and improving interoperability between sectors, technical teams and regulatory frameworks.
🔍 Differential value: Ensures that concepts such as "event", "probability", "impact" or "control" have the same meaning throughout the governance ecosystem.
ISO/IEC 22989:2022. Fundamental AI Terminology
It is the starting point for understanding what an AI system is. It defines concepts such as supervised learning, unsupervised learning, autonomous agents, symbolic reasoning, neural networks, etc. It establishes a taxonomy to classify technologies and harmonize their use.
🔍 Differential value: Favors regulatory and technical interoperability, avoiding ambiguities that affect risk management.
ISO/IEC 42005:2025. Social and ethical impact assessment
This standard represents a step forward in algorithmic governance. It provides guidelines for assessing how an AI system may affect individuals, collectives and societies. It introduces tools to analyze impacts on fundamental rights, inclusion, equity and security.
🔍 Differential value: Connects technology and human dignity. Incorporates mechanisms for transparency, traceability and documentation of decisions.
ISO/IEC 42001:2023. IA Management System (IMS)
First international standard that establishes requirements for implementing an IA management system in any organization. Addresses aspects such as responsibility, audit, accountability, efficiency and continual improvement.
🔍 Differential value: Equivalent to the "ISO 9001" of AI: creates an auditable and replicable framework for organizations developing or using AI.
Regulatory synergy: an interconnected system
These standards should not be viewed in isolation. They function as a regulatory regulatory ecosystem:
- ISO/IEC 23894 is based on ISO 31000 for its risk approach.
- Uses the common language of the Guide 73 and ISO/IEC 22989.
- ISO/IEC 42005 extends the analysis to social and ethical impact.
- ISO/IEC 42001 allows all of the above to be integrated into a structured management system.
This interweaving ensures coherence, avoids duplication and guarantees that the principles of fairness, transparency and responsible governance are present throughout the AI value chain.
Practical applications
Implementing these standards is not a bureaucratic exercise, but a strategic tool for:
- Detect and mitigate algorithmic biases
- Prevent security breaches or adversary attacks
- Foster public acceptance and public acceptance and trust
- Respond to regulators with documentary evidence
- Strengthen the institutional ethics
- Preparing organizations for future binding regulations, such as the EU's AI Act
Conclusion: towards a reliable and human AI
ISO standards are not one-size-fits-all recipes, but flexible guidelines that allow AI governance to be adapted to the sectoral, cultural and regulatory context. Applying them comprehensively improves not only the quality of AI systems, but also the confidence of the people and societies that use them.
Investing in standards is investing in confidence, security and the future.
Frequently Asked Questions:
What is ISO/IEC 23894:2023 and what is it for in AI?
ISO/IEC 23894:2023 provides guidelines for risk management in Artificial Intelligence systems. It covers the entire system lifecycle, from design to decommissioning, and integrates technical, ethical and social risk management. It is key to ensuring safe, reliable and responsible AI.
What does ISO 31000:2018 establish in the context of IA?
ISO 31000:2018 defines principles and a systematic approach to manage any type of risk within an organization. Although it is not exclusively focused on AI, it serves as a basis for structuring robust technology risk governance systems, including those arising from algorithms and automation.
What is the function of ISO Guide 73:2009?
ISO Guide 73:2009 standardizes risk management terminology. It defines key concepts such as "risk", "impact", "control" and "likelihood", allowing organizations to speak a common language in their risk assessment and mitigation processes.
What does ISO/IEC 22989:2022 bring to AI development?
ISO/IEC 22989:2022 establishes the fundamental concepts of Artificial Intelligence, such as machine learning, symbolic reasoning, neural networks or autonomous agents. It is essential to achieve interoperability between developers, regulators and industry sectors.
What is ISO/IEC 42005:2025 and what makes it innovative?
ISO/IEC 42005:2025 is a recent standard that guides the assessment of the social, ethical and human impacts of AI systems. It sets out how to identify, document and mitigate effects such as algorithmic discrimination, digital exclusion or decisional opacity.
What does ISO/IEC 42001:2023 regulate?
ISO/IEC 42001:2023 is the first international standard for IA management systems. It provides a structured framework for establishing, implementing, maintaining and improving an IA management system (IAMS), considering ethics, traceability, transparency and continual improvement.
Can the ISO AI standards be applied together?
Yes, the ISO standards for IA are designed to be complementary. For example, ISO/IEC 23894 builds on the principles of ISO 31000, uses the vocabulary of ISO Guide 73, incorporates the technical concepts of ISO 22989, and integrates within the management framework defined by ISO/IEC 42001. ISO/IEC 42005 adds the ethical and social dimension to this standards ecosystem.
Why apply ISO standards in Artificial Intelligence projects?
Applying ISO standards in AI allows anticipating risks, increasing public confidence, complying with future regulations (such as the European AI Act), documenting ethical processes, mitigating algorithmic biases and structuring automated decisions under principles of transparency and fairness.
How do ISO standards contribute to the ethical development of AI?
ISO standards embody principles such as fairness, safety, transparency, accountability and inclusiveness. They guide organizations to align technological development with human rights and social values, ensuring that AI benefits all of society.
Which organizations can implement ISO/IEC 42001?
Any public or private organization that develops, uses or manages Artificial Intelligence systems can implement ISO/IEC 42001. It is applicable to all sectors, from healthcare and banking to governments, universities or technology companies.
🔗 More information about ISO 31000 Standard
🔗 Watch our webinar on How to use Artificial Intelligence in Compliance.
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