AI is transforming the world of work, but without the right safeguards, its risks can be just as disruptive as its potential. ISO provides a foundation for secure and responsible AI adoption, helping organisations manage risks, align with regulations, and ensure the reliability and integrity of AI-driven systems. In this blog, we explore the crucial role of ISO in AI security and the key standards shaping its safe and effective implementation in business.
What is ISO?
The International Organization for Standardization (ISO) has been setting global benchmarks for safety, security, and efficiency since 1946, bringing together experts to establish best practices across industries.
ISO standards are widely respected in the business community, providing a trusted framework for quality, security, and compliance. In the field of artificial intelligence (AI), adherence to ISO standards helps organisations navigate regulatory requirements, mitigate risks, and promote responsible AI development.
Relevant ISO Standards for AI Implementation in Business
Successfully implementing AI in business requires a structured approach that covers every stage of the AI lifecycle. From defining core concepts and governance to managing risks, securing systems, and ensuring ongoing quality, ISO provides a clear framework for responsible AI adoption. An overview of the key ISO standards that can help your organisation implement AI effectively and securely.
ISO 22989: Defining AI Concepts and Terminology
The first step in any AI implementation is establishing a clear and shared understanding of its core concepts. ISO 22989 provides this foundation by defining key AI terminology and principles, ensuring consistency across industries, organisations, and regulatory frameworks.
By standardising how AI systems are described, classified, and evaluated, ISO 22989 supports the effective implementation of AI governance (ISO 42001), risk management (ISO 23894), security (ISO 27090), and quality assurance (ISO 25058).
AI Governance and Compliance
ISO 42001 is the first international standard for Artificial Intelligence Management Systems (AIMS), providing organisations with a structured framework for secure, transparent, and accountable AI management. It sets out guidelines for establishing, implementing, maintaining, and improving AI systems, addressing key challenges such as ethics, transparency, and continuous machine learning.
The standard integrates risk management, lifecycle governance, and data quality assurance, drawing on established frameworks and industry expertise. Designed to be auditable, ISO 42001 helps organisations demonstrate compliance, strengthen accountability, and manage AI responsibly across supply chains.
As AI continues to evolve, ISO 42001 supports organisations in developing resilient AI strategies that balance innovation with security and ethical responsibility. By adopting this standard, businesses can enhance trust, ensure regulatory alignment, and uphold best practices in AI implementation.
ISO 23894: AI Risk Management
As AI becomes more pervasive, ISO 42001 was introduced to provide a structured framework for establishing, implementing, and continuously improving AI management systems. This high-level standard lays the foundation for AI governance, addressing key principles such as transparency, accountability, and compliance. However, its broad scope means it does not delve deeply into AI-specific risks, making ISO 23894 essential for providing a structured approach to identifying, assessing, and mitigating these unique challenges.
ISO 23894 is specifically designed for AI risk management, recognising that while AI shares some risks with traditional software, its ability to learn from data, make autonomous decisions, and interact with the physical world introduces unique challenges.
Beyond risk identification, ISO 23894 serves as a strategic guide, offering practical frameworks for embedding risk management into AI-driven activities and business functions. It outlines AI-specific risk sources and provides concrete examples of effective implementation, ensuring organisations can customise their approach based on industry needs and operational contexts.
The interplay between ISO 42001 and ISO 23894 is fundamental to effective AI governance. While ISO 42001 sets the foundation by establishing the need for risk assessment, ISO 23894 provides the structured framework to address AI-specific risks in practice. Together, these standards give organisations a comprehensive approach to responsible AI management, ensuring AI technologies are secure, compliant, and aligned with both operational and ethical requirements.
ISO 27090: Securing AI Systems Against Emerging Threats
While ISO 42001 establishes AI governance and ISO 23894 focuses on risk management, ISO/IEC 27090 is specifically designed to address security threats unique to AI systems. Unlike traditional cybersecurity measures that focus on general IT infrastructure, this standard recognises that AI introduces new vulnerabilities that require specialised protections.
AI models are particularly susceptible to threats like evasion attacks, data poisoning, model stealing, and membership inference attacks, all of which can compromise the integrity, confidentiality, and reliability of AI systems. ISO 27090 provides organisations with a structured approach to identifying, mitigating, and monitoring these AI-specific security risks throughout the entire AI lifecycle.
What sets ISO 27090 apart is its integration of conventional cybersecurity principles. By treating AI as part of a broader information security ecosystem, this standard ensures that organisations not only manage (ISO 23894) and govern (ISO 42001) AI risks but also actively secure AI models, data pipelines, and decision-making processes against emerging threats.
As AI continues to be integrated into critical systems and business operations, ISO 27090 will play a crucial role in helping organisations fortify AI security, comply with evolving regulations, and maintain trust in AI-driven environments. When combined with ISO 42001 and ISO 23894, it provides a comprehensive, layered approach to AI governance, risk, and security management.
ISO 25055: AI Quality Evaluation
Once AI is implemented, continuous quality assessment is essential to maintaining trust, security, and performance. ISO 25058 provides a structured model for evaluating AI systems, enabling organisations to assess accuracy, robustness, resilience, and security with measurable criteria.
By offering practical methods to assess and refine AI performance, this standard helps ensure that AI systems remain trustworthy, effective, and aligned with organisational goals. Building on the foundations set by ISO 22989 and complementing the risk and security frameworks of ISO 23894 and ISO 27090, ISO 25055 reinforces a consistent and reliable approach to AI quality management.
The Roadmap for Responsible AI
As AI becomes more embedded in business operations, ensuring its responsible and secure implementation is essential. ISO provides a structured framework, guiding organisations through the complexities of AI adoption while addressing governance, risk, security, and compliance. By aligning AI strategies with these standards, organisations can ensure their AI initiatives are effective, ethical, and resilient, supporting long-term innovation while mitigating risks.
How CWSI Can Help
CWSI has a proven track record of guiding organisations through secure and responsible AI adoption. By aligning AI strategies with international standards and industry best practices, we help businesses maximise AI’s potential while mitigating risks and maintaining trust.
Whether you’re establishing AI governance, implementing risk management frameworks, or enhancing security measures, our experts provide tailored guidance and hands-on support to ensure a resilient AI strategy.
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