ISO 27090 Guidance for the application of ISO/IEC 27001 to AI systems

ISO/IEC 27090 is a standard under development titled "Information security, cybersecurity and privacy protection — Artificial intelligence — Guidance for the application of ISO/IEC 27001 to AI systems." Its primary purpose is to help organizations apply the internationally recognized ISO/IEC 27001:2022 Information Security Management System (ISMS) framework specifically to AI systems. It bridges the gap between traditional cybersecurity and AI-specific threats, such as data poisoning, model evasion, and adversarial attacks. Unlike ISO/IEC 42001, which establishes a comprehensive AI Management System (AIMS), ISO 27090 focuses specifically on the security dimension. It provides a practical pathway for organizations to implement security controls that demonstrate compliance with emerging regulations like the EU AI Act.

Enterprises can apply ISO 27090 in practice through a three-step process: 1. **AI-Specific Risk Assessment:** Extend the existing risk assessment process (based on ISO/IEC 27005) by identifying AI-specific threats using frameworks like the NIST AI RMF or MITRE ATLAS™. These unique risks, such as model theft or inference attacks, are then integrated into the corporate risk register. 2. **Control Adaptation:** Use ISO 27090's guidance to tailor ISO/IEC 27001:2022 Annex A controls for the AI context. For instance, access control (A.5.15) must be extended to model weights and training datasets, while change management (A.8.32) needs to cover the entire model retraining and deployment pipeline. 3. **Validation and Monitoring:** Establish continuous monitoring for AI systems to detect model drift, performance degradation, and anomalous outputs, aligning with ISO 27001's monitoring activities (A.8.16). Regular AI-focused red teaming exercises should also be conducted. This approach can measurably improve an organization's compliance posture against the EU AI Act and reduce AI-related security incidents.

Taiwan enterprises face three primary challenges when implementing ISO 27090: 1. **Interdisciplinary Talent Gap:** There is a significant shortage of professionals who possess deep expertise in both AI/ML and cybersecurity, making it difficult to accurately identify and assess novel AI-specific risks. 2. **Legacy System Constraints:** Many existing AI systems and MLOps pipelines were developed without a "Security by Design" approach, making it technically complex and costly to retrofit essential security controls like robust access management and logging. 3. **Immature Risk Methodologies:** Traditional IT risk assessment frameworks are often insufficient for quantifying the impact and likelihood of unique AI risks, such as algorithmic bias or data poisoning attacks. Solutions include forming cross-functional AI security teams, embedding security into the AI development lifecycle, and leveraging specialized frameworks like the NIST AI RMF to guide a more robust and relevant risk assessment process.

Winners Consulting specializes in ISO 27090 for Taiwan enterprises, delivering compliant management systems within 90 days. Free consultation: https://winners.com.tw/contact