AI Governance in Practice: What Organisations Should Actually Put in Place

Most organisations using AI already know the headline risks: bias, privacy, black-box decisions, and accountability gaps.

The real problem is not awareness. It is execution.

This article sets out practical governance steps organisations should already have in place — based on how AI is actually deployed in business and how risk is assessed in practice.

1. Start with an AI Use Register (Not a Policy)

Many organisations start with an “AI policy”. That’s usually the wrong first step.

What to do instead: Create an AI use register.

For each AI system (including third-party tools), document:

• purpose of the system

• whether it informs or makes decisions

• who relies on the output

• data inputs (personal, sensitive, confidential)

• whether outputs affect individuals

This reflects the risk-based approach in the governance framework and allows controls to be proportionate.

Why this matters: You cannot govern what you haven’t identified.

2. Classify AI by Impact, Not Technology

Governance should follow impact, not labels like “generative AI” or “machine learning”.

A useful classification:

• Low impact: internal analytics, productivity tools

• Medium impact: decision support with human review

• High impact: automated or near-automated decisions affecting individuals

This aligns with how risk increases when AI outputs are actioned or relied on without oversight.

Practical outcome: Different approval thresholds, review requirements, and escalation paths.

3. Assign Named Accountability (Not Committees Alone)

AI governance fails when “everyone” is responsible.

For each AI system, assign:

• an owner for business use

• an owner for data governance

• an owner for technical performance

• an owner for outcomes and impacts

These roles do not need to sit with one person, but they must be named and documented.

Why this matters: Accountability gaps are where legal and reputational exposure arises.

4. Build Human Review Deliberately into the Process 

AI should not silently replace judgment.

Organisations should:

• identify where human review is required

• document when AI outputs can be relied on

• specify when outputs must be challenged or overridden

This is particularly important for automated decision-making and content generation, where errors or bias can have real-world consequences.

Good governance question:
“If this output is wrong, who catches it — and how?”

5. Fix Vendor AI Risk at Contract Level

Vendor compliance does not equal customer compliance.

Contracts should clearly address:

• ownership and permitted use of input data

• whether customer data is used for training

• ownership or protection of outputs

• confidentiality of inputs and outputs

• audit and explainability rights

• liability allocation for AI-specific risks

This is especially important where AI systems evolve or self-learn over time.

Common gap: Standard SaaS terms that never anticipated AI use.

6. Document Decisions, Not Just Controls

Governance is not only about controls — it is about evidence.

Organisations should keep records of:

• why an AI system was adopted

• risk assessments performed

• key design or deployment decisions

• changes made over time

This supports transparency, accountability, and audit readiness.

7. Treat Generative AI as a Special Case

For internal generative AI tools:

• restrict what data can be uploaded

• document approved and prohibited use cases

• require review of outputs before use

• require material modification of outputs before external publication

These controls reduce privacy, IP and misinformation risk.

Practical Internal Checklist for Organisations

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Further information

If you need support with AI governance, risk management, or reviewing your current AI use, email hello@pixellegal.com.au or organise a free consultation.

Disclaimer

This article is provided for general information purposes only and does not constitute legal advice. It does not take into account your organisation’s specific circumstances, systems, or regulatory obligations. You should obtain tailored legal advice before taking action