How ISO/IEC 42006 Helps Companies Manage AI Model Risks?

 

Introduction

As organisations increasingly rely on AI models for decision-making, analytics and automation, the need to manage risks associated with AI becomes critical. ISO/IEC 42006 offers a framework to manage those risks systematically — helping companies ensure their AI deployments are responsible, transparent and dependable. A proper AI model risk management system reduces potential harm, supports compliance and builds stakeholder trust.

What ISO/IEC 42006 Covers?

  • Provides guidance on identifying, assessing and managing risks that arise when developing, deploying or maintaining AI models.

  • Covers documentation, governance, data quality, validation, monitoring and continuous evaluation across the AI model lifecycle.

  • Supports policies and controls to ensure data privacy, fairness, security and accountability when using AI systems.

  • Encourages regular audits and reviews of AI models to detect drift, bias, errors or unintended outcomes — ensuring that models remain aligned with organisational and ethical standards over time.

Why AI Model Risk Management Matters?

  • AI models often handle sensitive data and critical decision-making; unmanaged risk can lead to biased decisions, privacy breaches or compliance failures.

  • A structured risk-management framework helps organisations avoid reputational damage, regulatory scrutiny and operational losses.

  • It builds greater confidence among stakeholders — customers, partners or regulators — that AI systems are controlled, transparent and trustworthy.

  • Ensures AI models continue to perform reliably even as data or environments change, by monitoring for drift, bias or degradation.

Common Pitfalls to Watch Out For

  • Treating AI risk management as a one-time checklist instead of an ongoing, evolving process.

  • Skipping thorough validation and testing of AI models before deployment.

  • Relying on poor quality or biased data — which undermines model fairness and trustworthiness.

  • Failing to implement monitoring or periodic reviews — leading to model drift, degraded performance, or uncontrolled risk.

  • Lack of clear governance, documentation, accountability or ownership for AI models and their outputs.

How Pacific Certifications Can Help?

Pacific Certifications supports companies implementing ISO/IEC 42006 by helping them scope AI risk needs, set up governance structures, design validation and monitoring protocols, and prepare for assessments or audits. We guide you in embedding risk management — not as a one-off step — but as part of your continuous AI lifecycle management.

Read the full blog here: How ISO/IEC 42006 Helps Companies Manage AI Model Risks?

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