AI for Australian financial planners: what actually helps without breaking the rules

Financial planning is a heavily regulated profession, ASIC licensing, AFSL responsibilities, FOFA’s best-interests duty, the Privacy Act. AI helps where the work is mechanical (drafting, formatting, summarising), not where the work is regulated (giving advice).

Here’s what works without putting your licence at risk.

What AI is good at for planners

1. Fact-find synthesis

Client comes in with statements, tax returns, super fund letters, insurance policies, three different scanned wills. You used to hand this stack to a paraplanner for a day’s work building a single coherent picture.

AI can produce a first-pass synthesis much faster:

• Drops each document into Claude (paid API, not Claude.ai consumer)
• Extracts the structured data, assets, liabilities, income, super balances, insurance cover, dependants, beneficiaries
• Cross-references for inconsistencies (“the will lists 3 beneficiaries but the super beneficiary nomination only lists 2”)
• Outputs a structured client summary that goes into your CRM

You still verify everything. The hours saved are real.

2. ROA / SOA prep drafting

The Record of Advice or Statement of Advice still gets signed by you, vetted by your compliance officer, and bears your AFSL licence. But the first draft can be AI-assisted.

Prompt pattern:

You are helping draft an ROA for an Australian client. NOT GIVING ADVICE.
Drafting only, adviser reviews + signs.

Client context: {fact-find summary}
Recommendation made by adviser: {adviser's plain-English notes}
Compliance template: {your AFSL's ROA template}

Draft the ROA, populating:
- Client circumstances (from fact-find)
- Goals (from adviser's notes)
- Recommendation (verbatim from adviser's notes)
- Risks + alternatives considered
- Costs (use the placeholder ${COST}, adviser will fill)
- Why this is in the client's best interests (justification draft only)

Do NOT invent product names. Do NOT invent fees. Use placeholders where data is missing.

Treat the output like a junior paraplanner’s first draft: it needs the same senior review.

3. Post-meeting notes

Client meeting runs an hour. Recorded (with consent) via your CRM or via a tool like Read.ai / Fireflies. Transcript goes to Claude with a prompt to produce structured meeting notes:

• Key decisions made
• Action items (with owners)
• Open questions
• Next steps + dates

It removes most of the write-up work after each meeting.

4. Ongoing-service email cadences

For your retainer clients, you send periodic emails, market updates, regulatory changes, portfolio reviews, birthday wishes for review meetings. AI drafts these in your voice, you approve, you send (or schedule via your CRM).

Don’t auto-send. Even harmless emails benefit from your read because client relationships are why people pay you in the first place.

What AI is NOT good at (and what’s regulated)

• Giving financial product advice. AI cannot legally do this. Only an AFSL-licensed adviser can. AI drafts; you advise.
• Suitability assessments. The “is this product in the client’s best interests” judgment is the regulated bit. AI can structure the argument; you make the call.
• Compliance sign-off. Your compliance officer reviews; AI is not a substitute.
• Anything that gets emailed to a client without your sign-off. Even auto-acknowledgements. Especially auto-acknowledgements if the wording strays into advice territory.

Privacy + data handling

Australian Privacy Principles apply to all client data:

• Use paid API tiers (Anthropic Console, OpenAI API). Their data-retention contracts let you commercially use them with client-identifiable data.
• Don’t paste client data into consumer Claude.ai or ChatGPT. Consumer plans of ChatGPT (Free and Plus) and Claude (Free, Pro and Max) can use chats to improve models unless you switch that setting off; business plans (ChatGPT Business/Enterprise, Claude Team/Enterprise) and the APIs are not used for training by default.
• Strip identifiable data before AI processing where possible (rename “Jane Smith” → “Client A”, “$1.2m super” → “$Xm super”) and re-identify after.
• Document your AI use in your Privacy Policy and your AFSL’s procedures. Disclose to clients.

A typical tool stack

Tool	Monthly AUD	Role
Claude API (Sonnet 4.6)	$60-120	Drafting, synthesis
Xplan / AdviserLogic built-in AI	varies	Platform-native workflows
Fireflies / Read.ai	$30-60	Meeting transcription
Calendly	$0-25	Booking
Total new spend	$90-205 AUD/adviser

What to build first

Fact-find synthesis. Lowest regulatory risk (it’s data processing, not advice), biggest immediate time-back. Pick one upcoming new client, do the synthesis with Claude, compare to what your paraplanner would have produced manually.

If you want this set up for you, On Autopilot offers a free 30-minute AI audit. Your compliance officer or licensee still signs off the AFSL side.