Can AI write MLS listing descriptions

Two different questions hide inside this one, and they have opposite answers. Can you use an AI tool to help draft the description for your own listing? Generally yes — no Canadian board rule we have encountered prohibits it, and the tools are genuinely good at turning a feature list into readable prose. Can you point AI tools at MLS® data — other people’s listings, feed records, sold data — to generate content? That is where the wall is, and it is higher than most agents realize, because it is built into the data contracts rather than the public rulebooks. We operate on the licensed-feed side of Canadian real estate, so this page covers both halves first-hand.

Drafting your own listing: allowed, and entirely on you

When you prompt an AI with your own notes, your photos, and your seller’s information, you are using a writing tool, and the output is your advertising like anything else you publish. Which triggers the rule that actually matters: the registrant is responsible for accuracy, no matter who — or what — wrote the words. Ontario’s and BC’s conduct rules on misrepresentation do not have an AI exception, and AI text generators fail in exactly the way those rules punish: they invent specifics. A model will confidently produce square footage you never gave it, a “newly renovated kitchen” it inferred from a photo, or a “five-minute walk to the lake” it made up entirely. Treat every factual claim in a generated draft as unverified until you have checked it against your measurements and your seller’s disclosures. The efficient workflow is AI for structure and fluency, agent for every fact.

What remarks must never contain, whoever wrote them

The public remarks field carries its own board rules, and an AI does not know them. Remarks must not include personal information about the seller or occupants, and boards restrict things like contact details and showing instructions in public-facing fields. A model trained on American listing copy will also happily produce phrasing that describes the ideal buyer rather than the property — “perfect for a young family” — which walks into human-rights problems in Canadian advertising. Whatever drafts the text, the pre-publish read is a compliance read: facts verified, no people described, nothing in the field the board says cannot be there.

The wall almost nobody knows about: feed data and AI

Here is the first-hand part. The MLS® data agreements that put listing feeds on websites — the paperwork behind every IDX and VOW site — now contain sweeping AI restrictions. The TRREB-side agreements we sign as a technology vendor prohibit feed data from entering AI systems, defined broadly enough to cover sending a listing record to a language model, an embedding pipeline, or an AI-powered SaaS tool, and prohibit using AI to create derivative content from the feed. Feed fields in a prompt is a contract breach; so is “AI-summarize these MLS listings” as a website feature. This is why who owns MLS listing data matters practically: the data on your website is licensed, not yours, and the licence now names AI explicitly. It is also why BrokerFold’s own AI features are fenced off from board feed data entirely — the fence is a contract term, not a design preference.

Where the line lands for a working agent

Put the two halves together and the practical rules are short. Your own listing, from your own inputs: draft with AI freely, verify every fact, run the compliance read. Other listings pulled from an MLS system, a feed, or a portal: never into an AI tool — for the contractual reasons above and the copyright ones, since descriptions and photos are authored works, a point the scraping question makes at system scale. Market commentary is its own lane with its own board rules — see publishing market statistics — and generating it by pointing AI at feed data fails both lanes at once. The technology is allowed to hold the pen. The licence decides what the pen may touch, and you remain the byline either way.