Yes — you can use a general AI tool like ChatGPT, Claude or Microsoft Copilot as a property listing description generator, and for most agents in Australia it will cut a 20-minute writing job down to about five. Feed it the property facts, your tone and word count, and it drafts on-brand copy you then edit and fact-check. The catch is that the AI will happily write something that breaches your state's underquoting or misleading-representation rules if you let it. This article shows the prompts that produce good copy and keep you out of trouble.
This is for sales agents, property managers and marketing coordinators in Australian agencies who write their own listings and want to speed it up without handing a compliance problem to their principal. No technical skill needed.
Why AI is genuinely good at listing copy — and where it isn't
Listing descriptions are a near-perfect fit for AI. The structure is predictable, the tone is consistent across a brand, and the raw inputs (beds, baths, car, features, suburb) are things you already have. An AI model trained on billions of words is very good at turning a bullet list into fluent, varied prose that doesn't sound like the last twelve listings you wrote.
Where it falls down is anything that has to be true. AI generates plausible language, not verified facts. It will confidently describe a "north-facing entertainer's deck" when your notes never mentioned the aspect. It will invent "walking distance to the station" because that phrase appears in millions of listings. Every factual claim it produces is a draft to check, not a fact to publish.
That single distinction — fluent yes, factual no — is the whole game. Use AI for the phrasing and let a human own every claim.
What the law expects from a listing description in Australia
Two areas catch agents out, and both are enforced by state fair-trading regulators and, for conduct generally, the Australian Consumer Law.
Underquoting. Advertising a price or price guide lower than the agent's genuine estimate, the seller's asking price, or a rejected offer is prohibited. The rules differ by state — NSW, Victoria and Queensland each have their own regime, and some require a price to fall within a defined range or a single figure. AI has no idea what your agency agreement says, so it should never generate, suggest or "round" a price. Keep price entirely out of the AI step and add it manually against your compliance checklist.
Misleading or deceptive representations. You can't claim a feature, dimension, zoning, school catchment, rental return or renovation approval that isn't accurate. This is exactly the kind of confident-sounding detail AI invents. "Recently renovated," "council-approved granny flat," "strong rental yield" and "moments from the beach" are all claims someone can hold you to.
None of this is legal advice — check your own state's fair-trading guidance and your agency's compliance policy. The practical takeaway is simple: AI drafts the language, a licensed person verifies the claims.
The base prompt: a listing description generator you can reuse
Open ChatGPT, Claude, or Copilot inside your firm's Microsoft 365 tenant. Paste a prompt like this and fill in the brackets:
You are writing a property listing description for an Australian real estate agency. Write in Australian English. Tone: [warm and professional / upbeat / understated premium]. Length: [90–120 words]. Only use the facts I provide below — do not add features, measurements, locations, aspects, or claims I have not listed. Do not mention price. Property: [3 bed, 2 bath, 1 car; brick home; renovated kitchen 2023; fenced backyard; solar; suburb: X]. Highlight: [the kitchen and the yard]. End with a soft call to inspect.
The two instructions doing the heavy lifting are "only use the facts I provide" and "do not mention price." Those turn a creative writer into a disciplined one. Keep this prompt saved as a template — in a ChatGPT saved prompt, a Claude Project, or just a note you paste in each time.
What to type in order — and how to fix a bad first draft
The skill isn't the first prompt. It's reacting when the draft is wrong. Here's the sequence.
- Run the base prompt. Read the output against your source notes, line by line.
- Kill invented claims. If it wrote something you didn't feed it, reply: "You mentioned [north-facing / walking distance to shops]. I never stated that. Rewrite without it and without adding any location, aspect, or distance claims."
- Fix the tone. Too flowery? "Cut the adjectives by half. Make it sound like a confident agent, not a brochure." Too flat? "Add a little warmth to the opening line without exaggerating."
- Tighten length. "Trim to 90 words while keeping the kitchen and yard as the highlights."
- Ask for variants. "Give me three opening sentences I can choose from." Portals, social and the shopfront window all want slightly different lengths — generate them in one go.
Two or three rounds gets you there. If you find yourself fighting the same invented detail repeatedly, add it as a permanent "do not include" line in your base prompt.
Building an on-brand voice the AI will actually keep
Generic AI copy reads generically. To make it sound like your agency, give the model examples. Paste three of your best past listings and add: "Study the voice, rhythm and sentence length in these three examples. Write all future descriptions in this style." In Claude, save that as a Project; in a custom GPT, put it in the instructions. Now every draft starts closer to your brand and needs less editing.
A word of caution on those examples: use listings that are already published and contain no personal information about vendors or buyers — just the marketing copy.
Keeping client and vendor data out of the AI
Listing copy itself is usually low-risk, but the surrounding material isn't. Vendor names, contract details, reasons for selling ("deceased estate", "divorce", "must sell before settlement") and buyer feedback are all personal information, and the OAIC's general guidance is clear that you shouldn't paste personal information into publicly available AI chatbots.
Practical rules:
- Feed the AI property features, not people. It doesn't need a name to describe a kitchen.
- Use an enterprise or business tier where your inputs aren't used to train the model — Copilot inside your Microsoft 365 tenant, or Gemini in Google Workspace, keeps data within your own environment.
- Strip anything sensitive about why the vendor is selling before it goes anywhere near a prompt.
For the full picture on what's safe to enter and what isn't, see our guide on whether AI is safe for client data under the Australian Privacy Act.
A compliance checklist before you publish
Run every AI-drafted listing through this before it goes live. It takes under two minutes.
| Check | What to confirm |
|---|---|
| Facts | Every feature, measurement and year matches your source notes and the contract. |
| Claims | No "approved", "renovated", "walking distance", "school catchment" or yield claim you can't back up. |
| Price | Added manually, consistent with your agency agreement and your state's underquoting rules — never generated by AI. |
| Location | Suburb and nearby amenities are accurate; no invented proximity to transport or beach. |
| Aspect | Any orientation claim (north-facing, etc.) is verified, not assumed. |
| Sign-off | A licensed agent has read the final copy and owns it. |
The person who publishes the listing is responsible for it. AI doesn't change that, and "the AI wrote it" is not a defence to a fair-trading regulator.
When not to use AI for a listing
Skip it for a genuinely unusual property — heritage, rural holdings, complex zoning, mixed-use — where the value is in nuance the model won't grasp and is likely to get wrong. Skip it when the deadline is so tight you won't have time to fact-check; a fast wrong listing is worse than a slow right one. And don't automate publishing straight from AI to a portal. The human review step is the whole point.
Fitting this into the rest of your marketing workflow
A listing generator is one small piece. The same approach — AI drafts, human verifies — works for social captions, email campaigns to your buyer database and open-home follow-ups. If you're mapping out where AI fits across the agency, our overview of the top no-code tools every real estate agency should be using covers the connecting pieces, and AI email management for real estate agents handles the inbox side.
Start with one listing this week. Save the base prompt, add your brand examples, and run the compliance checklist. Once the pattern is habit, the writing takes minutes and the checking becomes second nature.
If you'd like more automations built the same careful way — draft with AI, verify with a human — our free guide 10 AI Workflows to Save 10+ Hours a Week walks through the highest-value ones for professional services and property firms.
Common questions
Can AI write property listing descriptions that comply with Australian law?
AI can write the copy, but it can't guarantee compliance on its own. It produces fluent language, not verified facts, and will invent features or claims if allowed. A licensed agent must fact-check every claim, add the price manually against underquoting rules, and sign off before publishing. Used that way, AI speeds up drafting without creating a compliance risk.
How do I stop AI from underquoting in a listing?
Keep price out of the AI step entirely. Add an explicit instruction like "do not mention price" in your prompt, then insert the figure manually once the copy is drafted, checking it against your agency agreement and your state's underquoting regime. AI has no knowledge of your vendor's genuine estimate or rejected offers, so it should never generate or suggest a price.
Which AI tool is best for generating real estate listings in Australia?
Any capable general model works — ChatGPT, Claude or Microsoft Copilot. For firms handling any client information, an enterprise or business tier is safer because your inputs aren't used to train the model. Copilot inside your Microsoft 365 tenant or Gemini in Google Workspace keeps data within your own environment, which suits agencies that already license those platforms.
Is it safe to paste vendor details into ChatGPT to write a listing?
No. Vendor names, reasons for selling and buyer feedback are personal information, and the OAIC's general guidance says you shouldn't enter personal information into publicly available chatbots. The AI only needs property features to write a description, not people's details. Strip anything sensitive first, and use a business-tier tool where your data isn't used for training.
How long does it take to generate a listing description with AI?
With a saved base prompt and your brand voice examples loaded, a first draft appears in seconds and usually needs two or three rounds of editing. Allow around five minutes for drafting plus a two-minute compliance check against your facts, claims, price and location. That's a large saving on writing from scratch, provided you never skip the verification step.
Want these ideas working in your firm? We build controlled AI workflows for Australian professional services firms — starting with a free automation audit.