Governance First: The CMO’s AI Marketing Risk Register (Sydney Boardroom Primer)

An AI marketing risk register is the fastest way to turn hype into governance your Sydney board will actually sign.
I built this primer so you can launch AI programs that are provable, compliant, and revenue-safe from day one.
You’ll get a ready-to-use register, a 30-60-90 rollout, and the exact controls I ask agencies to show me before I approve spend.

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What this is and why it matters

An AI marketing risk register lists the specific things that can go wrong, who owns each risk, and what evidence proves the control works.
It protects growth, your brand, and you.
Boards don’t fear AI.
They fear undocumented AI.

The 10-field template I actually use

Copy these fields into your register and you’re operational today.
Risk ID.
Description.
Owner.
Likelihood (1–5).
Impact (1–5).
Rating (L×I).
Controls in place.
SLA / Evidence.
Last test date.
Next review.

How often I review it

Weekly for operational risks.
Monthly for strategy and legal posture.
Quarterly for board-level assurance.
No meetings longer than 30 minutes.

Legal baseline in Australia you must respect

Anchor your register to the Privacy Act 1988 and the Australian Privacy Principles (APPs).
Map collection, notice, use/disclosure, direct marketing, cross-border disclosure, and security to APPs 3, 5–8, and 11. OAIC+1

Spam Act reality for lifecycle marketing

Every send must prove consent, accurate sender identity, and a functional unsubscribe that works for at least 30 days and is actioned within 5 working days.
Use ACMA’s unsubscribe fact sheet as your control reference and store screenshots. ACMA

Notifiable Data Breaches (NDB) clock

Your register needs a 30-day assessment clock for suspected eligible breaches and “as soon as practicable” notifications if confirmed.
Make the timer visible in your incident playbook. OAIC+1

Cross-border data and vendor responsibility

If personal information goes offshore, you remain accountable for how the overseas recipient handles it under APP 8 and s 16C.
Document locations, contracts, and tests. OAIC+1

Privacy Impact Assessments (PIAs) as a control, not theatre

Run a PIA for any new or materially changed AI personalisation or data use.
Attach the PIA summary to each risk the project touches. OAIC+2OAIC+2

Data mapping and lineage risk

If you can’t answer who/what/why/where/how long for each data field, you can’t govern it.
Keep a live data map with owners and proofs.
No proof, no activation.

Consent, notices, and preference risk

Record how consent was captured and what notice was shown.
Version notices like code.
If you change the purpose, update notice and re-confirm where required.

Unsubscribe failure risk

Automate tests that click real links and log outcomes.
Alert when action exceeds 5 working days.
Zero tolerance for send-after-unsub.

Model risk: hallucinations, bias, and drift

Define allowed sources and banned claims.
Use human-in-the-loop on sensitive outputs.
Log prompts, citations, and post-publish corrections.

Content IP risk

Ban unlicensed assets.
Store licenses and model terms with each deliverable.
If in doubt, replace with owned or permissive sources.

Identity and impersonation risk (SMS/email)

Register sender IDs where applicable and lock down spoofing vectors.
Rotate DKIM/DMARC reporting to marketing + security.
Treat brand impersonation as a crisis scenario.

Measurement and attribution risk

Bad attribution hides bad decisions.
Freeze KPI definitions for the pilot.
Use a holdout or geo split to prove incrementality.
Kill any dashboard that can’t export the math.

Brand and reputational risk

Define off-limits topics and tone.
Attach an editorial policy to the register.
If a post is corrected, keep the correction log public.

Vendor and toolchain risk

Contract audit rights for consent ledgers and unsub logs.
Require export proofs before go-live.
Map every sub-processor and where they run.

Operational risk: agents without owners

AI agents need named humans.
One owner per workflow.
Weekly output, error, and cost per asset tracked.
No orphaned automation.

Incident response you can run under pressure

Pre-write breach comms and stakeholder lists.
Timebox decisions.
Run a live drill every quarter.
Store lessons learned inside the register.

Sydney enforcement reality check

ACMA has issued multi-million-dollar penalties for unsubscribe failures and sending promos inside “transactional” emails.
Use recent cases as your training deck. News.com.au

The 30-60-90 rollout I give boards

Days 1–30.
Publish the risk register and owners.
Ship data map, consent ledger, unsubscribe QA, and the NDB clock.
Run a PIA on the first AI use-case. OAIC
Days 31–60.
Add cross-border controls.
Instrument attribution and a clean holdout.
Stand up agent workflows with human gates. OAIC
Days 61–90.
Run an incident drill.
Present board dashboard with performance + compliance KPIs.
Approve scale or fix.

How to score each risk (simple heatmap)

1–5 likelihood × 1–5 impact = 1–25 rating.
1–5 = Low (monitor).
6–12 = Medium (tighten controls).
13–25 = High (pause until mitigated).
Green, amber, red.
No gray.

Example entries you can paste

R-07 Unsubscribe failures.
Owner: Lifecycle Lead.
Risk: Non-functional link or >5-day action.
Control: Automated test suite + manual weekly QA.
Evidence: Logs + screenshots.
SLA: 5 working days. ACMA

R-12 Cross-border disclosure.
Owner: Data Protection Officer.
Risk: Offshore processing without APP-aligned safeguards.
Control: Contractual clauses + vendor audit + location inventory.
Evidence: DPA, pen test attestation, data-flow diagram. OAIC

R-18 NDB response.
Owner: CISO.
Risk: Late assessment/notification.
Control: 30-day timer + playbook + comms templates.
Evidence: Drill results. OAIC

KPIs I put next to the register

Revenue per marketing dollar.
Non-brand organic growth.
SQLs and win rate.
CAC and payback.
Unsubscribe SLA, complaint rate, zero send-after-unsub incidents.
PIA completion rate and last test dates.

FAQs

What is an AI marketing risk register in practice?
A living list of risks, owners, controls, and evidence tied to your AI programs and channels.

Who should own it?
You as CMO own the register.
Legal, security, data, and lifecycle leads own individual risks.

How often should we update it?
Weekly for execution risks.
Monthly for legal and vendor posture.
Quarterly for board assurance.

Do we need a PIA for every experiment?
Run a PIA for any new or materially changed use of personal information.
Attach the summary to related risks. OAIC

How do we prove spam-law compliance?
Store consent evidence, sender identity templates, and unsubscribe proofs with timestamps.
Audit monthly. ACMA

What goes into the incident playbook?
Severity tiers, roles, the 30-day NDB timer, draft comms, and a press/board path. OAIC

How do we handle offshore tools?
Document locations and contracts.
Bind vendors to APP standards under APP 8 and s 16C. OAIC

Can we run agent workflows without adding headcount?
Yes, if each agent has a human owner and weekly QA.
No owner means no agent.

What metrics satisfy the board?
Revenue, CAC, payback, organic lift, SQLs, plus compliance health and last-test dates.

What’s the biggest current enforcement theme?
Unsubscribe failures and promotional content inside “transactional” emails.
Test weekly. News.com.au

Conclusion

Governance-first AI marketing is not bureaucracy.
It’s how Sydney CMOs scale growth, protect brand trust, and pass any board scrutiny on command.
Start with the risk register, ship the controls, and show the evidence.
That’s how you operationalize AI without betting the company.
Use this AI marketing risk register to brief your team this week, and govern with confidence.
Book a demo at https://hoook.io to see how our customers getting up to 100% traffic growth and up to 20% revenue increase.

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