DISC InfoSec blog ISO/IEC 42001:2023 - from establishing to maintain an AI management system

Jul 02 2025

ISO/IEC 42001:2023 – from establishing to maintain an AI management system

Category: AI — disc7 @ 12:06 pm

AI businesses are at risk due to growing cyber threats, regulatory pressure, and ethical concerns. They often process vast amounts of sensitive data, making them prime targets for breaches and data misuse. Malicious actors can exploit AI systems through model manipulation, adversarial inputs, or unauthorized access. Additionally, lack of standardized governance and compliance frameworks exposes them to legal and reputational damage. As AI adoption accelerates, so do the risks.

AI businesses are at risk because they often handle large volumes of sensitive data, rely on complex algorithms that may be vulnerable to manipulation, and operate in a rapidly evolving regulatory landscape. Threats include data breaches, model poisoning, IP theft, bias in decision-making, and misuse of AI tools by attackers. Additionally, unclear accountability and lack of standardized AI security practices increase their exposure to legal, reputational, and operational risks.

Why it matters

It matters because the integrity, security, and trustworthiness of AI systems directly impact business reputation, customer trust, and regulatory compliance. A breach or misuse of AI can lead to financial loss, legal penalties, and harm to users. As AI becomes more embedded in critical decision-making—like healthcare, finance, and security—the risks grow more severe. Ensuring responsible and secure AI isn’t just good practice—it’s essential for long-term success and societal trust.

To reduce risks in AI businesses, we can:

Implement strong governance with AIMS – Define clear accountability, policies, and oversight for AI development and use.
Secure data and models – Encrypt sensitive data, restrict access, and monitor for tampering or misuse.
Conduct risk assessments – Regularly evaluate threats, vulnerabilities, and compliance gaps in AI systems.
Ensure transparency and fairness – Use explainable AI and audit algorithms for bias or unintended consequences.
Stay compliant – Align with evolving regulations like GDPR, NIST AI RMF, or the EU AI Act.
Train teams – Educate employees on AI ethics, security best practices, and safe use of generative tools.

Proactive risk management builds trust, protects assets, and positions AI businesses for sustainable growth.

ISO/IEC 42001:2023 – from establishing to maintain an AI management system (AIMS)

BSI ISO 31000 is standard for any organization seeking risk management guidance

ISO/IEC 27001 and ISO/IEC 42001, both standards address risk and management systems, but with different focuses. ISO/IEC 27001 is centered on information security—protecting data confidentiality, integrity, and availability—while ISO/IEC 42001 is the first standard designed specifically for managing artificial intelligence systems responsibly. ISO/IEC 42001 includes considerations like AI-specific risks, ethical concerns, transparency, and human oversight, which are not fully addressed in ISO 27001. Organizations working with AI should not rely solely on traditional information security controls.

While ISO/IEC 27001 remains critical for securing data, ISO/IEC 42001 complements it by addressing broader governance and accountability issues unique to AI. The article suggests that companies developing or deploying AI should integrate both standards to build trust and meet growing stakeholder and regulatory expectations. Applying ISO 42001 can help demonstrate responsible AI practices, ensure explainability, and mitigate unintended consequences, positioning organizations to lead in a more regulated AI landscape.

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