AI is rewriting the rules of real estate, but only if you’re prepared to use it correctly

Artificial intelligence (AI) has moved into the real estate sector so quickly that many agents still view it as a novelty. Yet behind the scenes, AI already shapes how top performers market, prospect, and communicate. First National's Stewart Bunn explores how the nation’s best-performing agents are using AI, and how others are still falling victim to costly mistakes.

The divide is not about who is “using” AI. Nearly everyone is. It’s about who is doing so strategically, deliberately, and safely.

Those who treat AI as a productivity engine are outpacing their competitors. Those who consider it a shortcut are finding themselves publishing embarrassing errors, breaching compliance rules, or facing uncomfortable conversations with regulators.

Needless to say, these are costly mistakes in a market where listings are tight and margins are constantly squeezed.

First National’s communications and corporate affairs manager, Stewart Bunn, has watched this split emerge in real time. Speaking with Real Estate Business (REB), he says AI has already become one of the industry’s most powerful differentiators, but only for agents who inherently appreciate its limitations.

Behind many of Australia’s top-performing agents is a daily workflow powered quietly by AI. Sharper listing copy, tailored marketing campaigns and polished administrative work are the obvious benefits.

However, one of the biggest advantages is the way AI transforms market research, aligning agent knowledge with vendor expectations from the first introduction meeting.

A quiet edge: How agents are using AI before they meet the vendor

According to the real estate veteran, the new competitive edge is rooted in intelligence: the ability to walk into a lounge room not just with a comparative market analysis (CMA), but with a clearer sense of who the client is, what matters to them, and how best to speak to their target buyers.

Knowing what makes the vendor tick is key to getting listings, and knowing the market is the key to a precise campaign.

“AI lets agents walk in to a listing appointment better prepared,” Bunn says. “They have a clearer idea of who the client is, how they might market the property, and who the target audience could be.”

Agents are no longer guessing which campaign structure will resonate, or which buyer demographic is most active. They can research behavioural patterns, analyse local demand, explore recent search trends and understand what buyers care about in that suburb right now.

The result is a listing pitch that feels unusually personalised, and a client who feels unusually understood.

A key differentiator among a price-conscious and sceptical clientele.

Some agents are even using AI to examine communication styles that speak directly to the target audience based on publicly available information.

Bunn stresses that this should be handled responsibly, but notes says that when used appropriately, it allows agents to create ultra-targeted campaigns that align vendor and buyer expectations.

“The insights help agents come across more informed,” he says. “Buyers notice that at open homes, and vendors notice buyers noticing.”

But it’s a double-edged sword. So, what happens when AI goes wrong?

As AI becomes more embedded in daily workflows, the risks become harder to ignore, as agents and marketing managers grow increasingly reliant on AI.

At its mildest, AI misuse results in robotic listing descriptions or embarrassing copy-and-paste mistakes. But at its worst, it produces incorrect statements, privacy breaches, misleading advertising, or even copyright violations. And it’s the agent that will pay the price.

Bunn has seen examples across the spectrum.

“It’s shocking when agents charge for their expertise but don’t even check their ads,” he says. “AI can speed up the process, but it can’t replace competence.”

One of the biggest dangers is when agents let AI make decisions for them. Tenant selection tools, for instance, can generate biased or inaccurate recommendations if not carefully monitored. AI-written business profiles can include claims an agency can’t legally back up. And content scraped or generated from unknown sources can easily breach copyright.

Regulators are paying attention, and Bunn expects scrutiny to increase.

“If you fail to fact-check advertising copy or client communications, you risk misleading or deceptive conduct,” he says. “That’s not a hypothetical risk, that’s real exposure.”

Privacy is another escalating concern. When agents upload tenancy applications, ID documents or sensitive vendor details into public AI platforms, they risk breaching privacy laws or internal compliance standards. Even when the intent is innocent, the consequences can be severe.

Let AI handle what it’s built for, and let us humans do what we do best

For all its capabilities, AI struggles with one of the most emotionally complex parts of real estate: managing conflict.

Responding to negative reviews is a perfect example, according to the communications and corporate affairs expert. AI can draft a polite reply, but it cannot understand human frustration, context, or motivations, and cannot de-escalate a tense situation, turning conflict into a win-win situation for all involved.

“The art of responding to disgruntled customers is completely missed by AI,” Bunn says. “When you learn the full context of a complaint, the right response can be very different from what AI would suggest.”

Agents often face reviews fuelled by emotion rather than fact. These situations call for diplomacy and human nuance, not a generic apology. A well-judged response can even persuade a dissatisfied client to remove an unfair review or see an agent’s perspective, something AI simply cannot accomplish.

Vendor education and negotiation are similarly delicate. AI may support the process by summarising information or offering draft explanations, but the persuasion, empathy and trust-building must still come from the agent.

Fixing the industry’s biggest problem: A breakdown in comms… from the agent

Few problems are more pervasive in the real estate industry than unanswered enquiries. For years, consumers have criticised slow replies, generic responses, or complete silence after submitting an enquiry.

AI eliminates the excuses. It can prepare responses instantly, maintain tone, personalise communication, and follow up consistently, even when the agent is otherwise engaged at an open home.

“The best agents are using AI to reply faster and with more empathy,” Bunn says. “It’s one of the most common areas where the industry is criticised.”

These faster touchpoints don’t just please buyers. They reassure vendors, who increasingly judge agents on responsiveness. When enquiries are handled well, it sends a message that a campaign is being run professionally from the first moment.

AI: Changing the way vendors find agents and how buyers find property

The next frontier is not how agents use AI, but how AI uses agents.

Platforms like ChatGPT and Google’s Gemini are increasingly delivering direct answers to property questions. Instead of sending users to external websites, they summarise responses on the spot. Agencies that haven’t structured their online data risk being filtered out of these AI-generated results entirely.

Bunn experienced this shift firsthand.

“After years of getting our offices into the top three Google positions, I panicked became alarmed when I saw some weren’t appearing in ChatGPT search at all,” he says. “AI wants structured, consistent data.”

In practice, this means agencies must maintain accurate statistics, updated online profiles, verified business information, and a consistent digital presence. Agencies that allow their data to drift risk becoming invisible to AI-driven search, and therefore invisible to consumers.

The future of digital visibility will belong to businesses whose information is clear, structured and accurate. For real estate, the implications are enormous.

Given all of this, how can you use AI? With AI governance and corporate policy!

Most AI mishaps are not caused by bad actors. They come from teams using AI without training or standards. Bunn believes every agency should implement clear guidelines that explain what can be uploaded, what must be checked, and what cannot be delegated to a machine.

Lack of governance doesn’t just invite mistakes; it creates confusion, inconsistency, and unnecessary risk. Strong AI policies, on the other hand, make work safer and faster. They reduce second-guessing, provide clarity and protect the brand while giving agents confidence in their processes.

Bunn emphasises that training is just as important as policy. Agents should understand legislative constraints, advertising standards and privacy requirements, especially as consumers increasingly use AI tools themselves.

He recalls one agent who received a string of aggressive, AI-generated legal threats from a frustrated client, citing a number of pieces of legislation.

A headache that can only be overcome by a technical mastery of the real estate profession.

AI is a tool, not the agent

The greatest value of AI in real estate often comes from the simplest tasks. It can triage enquiry emails, summarise complex threads, prepare tailored follow-ups, generate proposals, organise notes and keep conversations warm when the agent is on the road. Clients feel better serviced, agents feel more supported, and agencies feel the lift in productivity across every touchpoint.

But none of these benefits replace the agent. They amplify them.

When AI is paired with strong governance, thoughtful marketing, accurate data and clear rules, it becomes a hidden efficiency engine.

The agencies that thrive in the next decade will be those that strike this balance: human-led, AI-enabled, and tightly governed.

For the ones who ignore it, the danger isn’t that AI will replace them. It’s that their competitors will, armed with better tools, stronger processes and a deeper understanding of how modern consumers make decisions.

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