📜 Annex A.2: Policies Related to AI

Objective: To provide management direction and support for AI systems according to business requirements, and relevant legal, statutory, regulatory, and contractual requirements.

Policies are the backbone of any management system, and for an AI Management System (AIMS) under ISO 42001, they are non-negotiable. Control A.2 requires organizations to establish clear, actionable policies that guide how AI systems are developed, used, monitored, and retired. These policies set the tone for ethical, responsible, and compliant AI adoption from the top down.

✅ Why Policies are Crucial for AI Governance

AI technologies bring immense opportunities but also introduce complex risks like algorithmic bias, privacy violations, regulatory breaches, and reputational harm. Without strong, documented policies:

• Strategic Misalignment: AI projects may conflict with core business goals or ethical values.
• Ethical Blind Spots: Principles like fairness and transparency can be overlooked in the rush to innovate.
• Compliance Failures: The organization may fail to meet legal and regulatory obligations (e.g., EU AI Act).

By defining clear AI policies, management provides essential direction, aligns AI systems with business requirements, and builds lasting trust with customers, regulators, and other stakeholders.

🛠️ How to Implement Control A.2

Implementing this control involves a structured approach to policy management:

1. Define and Approve an AI Policy: This foundational document should be approved by top management and cover:
   • The business objectives that AI systems are intended to support.
   • The organization’s commitment to ethical principles (e.g., fairness, transparency, accountability).
   • Clear expectations for legal and regulatory compliance.

2. Integrate with Existing Governance: Don’t create policies in a silo. Ensure your AI policy integrates seamlessly with existing frameworks, such as your Information Security Management System (ISMS), Quality Management System (QMS), and overall risk management processes.

3. Communicate and Train: A policy is only effective if people know it exists. Communicate the policy to all relevant personnel and stakeholders. Provide training to ensure employees understand their responsibilities in upholding it.

4. Review and Update Regularly: AI technology, risks, and regulations (like the EU AI Act) evolve rapidly. Establish a process to review and update the AI policy at planned intervals or when significant changes occur.

💡 An Auditor’s Perspective

When auditing Control A.2, auditors look for evidence that policies are not just documents on a shelf but are living, breathing parts of the organization’s culture.

✅ What Auditors Like to See (Good Practices):

• Clear Alignment: Policies are explicitly linked to corporate values and business objectives (e.g., “Our AI will augment human decision-making, not replace accountability”).
• Top-Level Endorsement: Evidence of board-level or senior management review and approval of AI policies.
• Regular Reviews: A documented process for periodically reviewing and updating policies to keep them relevant.

⚠️ Common Audit Findings (Pitfalls):

• “Shelfware” Policies: The policy exists but has not been communicated, and employees are unaware of it.
• Generic Templates: The policy is a copy-paste from a template and is not tailored to the organization’s specific AI use cases, risks, or context.
• Disconnected Governance: The AI policy is not linked to the organization’s risk assessments or operational controls.

🎯 Conclusion

Control A.2 is fundamental to building a trustworthy AI Management System. It ensures that AI is not adopted in an ad-hoc or uncontrolled manner, but under a structured governance framework defined by clear policies. These policies act as a guiding compass, aligning AI innovation with business needs, regulatory obligations, and non-negotiable ethical standards.

In tomorrow’s article by Kimova.AI, we’ll explore Annex A.3 – Internal Organization, and discuss how to establish clear roles, responsibilities, and authorities for AI governance.