An AI Policy Is Not AI Governance: Seven Imperatives to Govern AI

⚡ Quick Summary

Published by Australian law firm MinterEllison, An AI Policy Is Not AI Governance provides executive and board-level guidance on translating static AI policies into operational, risk-tiered governance practices. The revised edition reflects significant regulatory milestones in Australia, including the National AI Plan, the Department of Industry, Science and Resources' AI Essential Practices (AI6), and upcoming transparency requirements for automated decision-making under privacy reforms. The guide details seven foundational imperatives designed to help enterprises establish clear operational boundaries, assign organizational accountability, calibrate risk appetites, institutionalize lifecycle assessments, reinforce data and intellectual property protections, monitor post-deployment performance, and control third-party procurement risk.

🧩 What's Covered

The report outlines seven structural imperatives that establish resilient governance architectures for AI adoption:

Imperative 1: Set the boundaries. Standardizing organizational terminology (distinguishing models, systems, use cases, developers, and deployers using ISO/IEC 42001 and NAIC standards), defining framework scope, and agreeing on foundational ethical principles such as fairness, transparency, and human oversight.
Imperative 2: Assign accountability. Establishing named oversight at the board and executive level while defining explicit operational decision rights, escalation pathways, and resource allocation across business units.
Imperative 3: Set risk appetite. Formalizing an organization-wide default posture that clearly classifies AI use cases into those encouraged, tolerated with safeguards, or prohibited entirely.
Imperative 4: Implement risk-based assessment and approval processes. Maintaining an enterprise inventory and central registry of AI use cases and applying proportional, multi-stage risk assessments across the system lifecycle.
Imperative 5: Strengthen data, privacy, and IP controls. Safeguarding data provenance, proprietary IP, and confidential information, while adapting to statutory privacy torts and evolving regulatory thresholds.
Imperative 6: Establish guardrails, monitoring, and assurance mechanisms. Conducting pre-deployment acceptance testing, monitoring post-deployment model drift and performance metrics, defining human-in-the-loop intervention criteria, and maintaining decommissioning procedures.
Imperative 7: Govern procurement and third-party AI risk. Conducting enhanced vendor due diligence, establishing contractual audit rights, and managing downstream exposure from embedded or externally hosted AI tools.

The report also outlines specific expectations for boards of directors regarding oversight, reporting lines, independent maturity reviews, and emerging legal considerations surrounding autonomous, agentic AI systems.

💡 Why it matters?

With Australia confirming it will govern artificial intelligence through existing legal frameworks (such as privacy, consumer protection, and directors' duties) rather than a standalone AI Act, liability falls directly on enterprise leadership. This resource moves beyond high-level principles to provide a legally grounded, practical blueprint. It illustrates how organizations can prevent compliance bottlenecks, avoid shadow AI adoption, and establish enabling governance infrastructure that balances risk management with enterprise innovation.

❓ What's Missing

The document is an executive-level strategic guide rather than an exhaustive implementation manual. It does not provide ready-to-use technical metric thresholds, complete risk assessment scoring matrices, or granular contractual boilerplate templates for vendor negotiation. Additionally, while it highlights the heightened compliance challenges introduced by agentic AI workflows, comprehensive guidance on governing multi-agent orchestration is reserved for a future publication.

👥 Best For

Corporate board members, Chief Risk Officers, General Counsel, Chief Privacy Officers, AI Governance Leads, and procurement directors navigating Australian regulatory frameworks and looking to operationalize AI management systems across their enterprise.