Can ChatGPT Tell You If A Melbourne Property Is A Good Buy? Where AI Gets Property Advice Wrong

Artificial intelligence has changed the way people research property.

Today, buyers can ask ChatGPT, Claude and other AI tools almost anything.

• What is this property worth?
• Is this a good investment?
• What suburb should I buy in?
• Should I buy now or wait?
• What should I offer?

The answers often sound convincing. Sometimes they are even correct.

The problem is that Melbourne property is one of the most nuanced markets in Australia. A property decision isn’t made purely from data. It’s made from context, experience, negotiation skill and local knowledge.

At LP Advisory, we regularly use AI as part of our research process. It is a fantastic tool for gathering information and understanding broad trends.

What it cannot do is inspect a property, read a selling agent, understand buyer behaviour at an auction or identify opportunities that aren’t obvious in the data.

Here are seven property questions where AI can often get the answer wrong — and where the experience of a buyers agent Melbourne buyers trust makes a real difference.

1. What Is This Property Worth?

This is probably the most common property question home buyers ask AI.

The challenge is that AI generally relies on publicly available information, previous sales data and comparable properties.

What it cannot always see is what has changed.

A property that sold five years ago for $1.2 million may now be worth $1.8 million because it has undergone a substantial renovation, added an extension, improved the floorplan or transformed its appeal to owner-occupiers.

Likewise, a property may appear good value online but have hidden issues that significantly impact its true market value.

We often see buyers rely on automated estimates only to discover they are comparing a renovated home with an unrenovated sale or vice versa.

Valuation is rarely just about numbers. It is about demand, presentation, competition, scarcity and how buyers perceive the property in today’s market. According to the CoreLogic Home Value Index, Melbourne has seen significant price variation across different property types and locations — reinforcing why comparable sales require careful interpretation.

2. Is This A Good Investment Property?

AI is excellent at analysing statistics.

It is much less effective at assessing real-world buyer demand.

Many AI tools focus heavily on rental yield, population growth, vacancy rates, infrastructure spending and historical performance.

While these metrics matter, they don’t tell the full story.

We’ve seen recommendations that looked strong on paper but were located on major roads, in oversupplied apartment precincts or within buildings that had significant owners corporation concerns.

One of the biggest mistakes property investors make is assuming that good data automatically equals a good investment.

In our experience, the strongest long-term investments are usually properties that owner-occupiers would also compete strongly for. That is much harder to measure in a spreadsheet.

3. Find Me The Best Suburb To Buy In Melbourne

This question sounds simple.

The reality is there is no single best suburb.

The right suburb depends on your goals, budget, borrowing capacity, risk profile and time horizon.

More importantly, AI often analyses property at a suburb level when experienced buyers analyse it at a street level.

In Melbourne, two properties within the same suburb can perform very differently over time.

One street may be tightly held with strong owner-occupier demand. Another may back onto industrial land, public housing, a major road or future high-density development.

The suburb is only part of the story. The street, position and property itself often matter more.

The REIV Market Insights data consistently shows how dramatically results can vary within the same postcode — something AI-generated suburb summaries rarely capture with enough nuance.

4. Should I Buy This Apartment?

This is where AI can become particularly misleading.

An apartment may appear attractive because the price looks affordable, the rental yield is strong or the suburb has performed well historically.

What AI often struggles to identify are the building-specific risks: significant owners corporation issues, future capital works requirements, defect history, poor floorplans, excessive investor concentration and oversupply within the building.

Two apartments in the same suburb can produce completely different outcomes depending on the building.

This is one reason we spend significant time analysing apartment buildings, not just apartment locations. If you’re relying on AI for this kind of assessment, you’re working without some of the most important information available.

5. What Should I Offer?

This is one of the questions AI struggles with most.

Property negotiations are not mathematical equations. They’re human interactions.

The right offer depends on vendor motivation, competing buyers, agent strategy, market sentiment, auction interest and timing.

A recent example from our full-service search work involves a property we identified for a client in Footscray. The quoted range was $800,000–$880,000. We were approached pre-auction with an offer opportunity at $870,000. After reviewing the campaign carefully — the level of interest, how the agent was managing buyers and the vendor’s position — we advised our client to decline and wait for auction day.

The property passed in. We then negotiated directly with the selling agent and secured it for $842,000.

No algorithm was reading the room that day. That outcome came from experience, timing and knowing when not to move.

6. Is This Property Overpriced?

One of the most interesting examples from recent years was a property we purchased in Richmond.

At first glance, some buyers saw it as an expensive two-bedroom home.

What many missed was the size and flexibility of the existing floorplan. The layout provided the opportunity to create a three-bedroom, two-bathroom home within the existing footprint while retaining off-street parking — a feature that is highly sought after in Richmond.

The market value wasn’t simply based on what the property was. It was influenced by what it could become.

That type of opportunity is often difficult for AI to identify because it requires interpretation rather than data analysis. It’s the kind of insight a buyers advocate Melbourne brings from hands-on experience in the local market.

This is also why we’ve written in more depth about Is A Buyers Agent Worth It In Melbourne? — because the value is most visible in exactly these moments.

7. Can AI Find Hidden Opportunities?

Unlike a search algorithm, finding off-market property requires relationships — and that’s something AI simply cannot replicate.

At LP Advisory, we have a dedicated off-market team that specifically calls hundreds of local Melbourne agents on a weekly basis. Their sole focus is uncovering new off-market opportunities before they ever reach the public market. These are relationships built over years — and in many cases, decades — that give our clients access to properties that never appear on any portal.

A recent example was a property we secured in Middle Park for just over $5 million. We were able to secure it through a relationship one of our team has maintained with a local agent for over 20 years. The vendor avoided all of the costs and disruptions that come with a public campaign — no marketing, no styling, no carrying an empty property through weeks of open homes and negotiation. And for our client, the outcome was exceptional. An updated version of the same home just two doors down subsequently sold on the open market for over $7 million — demonstrating just how significantly below true market value our client acquired their property.

Another example that highlights the real cost of on-market competition was an apartment we secured in Hawthorn for $650,000 — purchased off-market, quietly, with no competing buyers. Just five weeks later, an apartment with the same floorplan in the same building went to auction. Four bidders competed. It sold for $750,000.

That $100,000 difference wasn’t about the property being worth more — it was about competition inflating the price. When multiple buyers are bidding for the same asset, emotion and fear of missing out drive the outcome. Off-market purchases remove that dynamic entirely.

No AI tool can build the relationships that generate these kinds of opportunities. It can’t make hundreds of calls each week. It can’t draw on 20 years of trust with a local agent. That is where our team makes a difference that no algorithm can replicate.

These are the opportunities that often separate average outcomes from exceptional ones. We explore this further in our guide on How A Buyers Advocate Saves You Money.

What AI Gets Right

To be clear, we are not anti-AI. We use it ourselves.

AI is incredibly useful for understanding property terminology, researching suburbs, learning about the buying process, summarising market reports and generating questions to ask professionals.

Used properly, it can help buyers become far more informed. The mistake is assuming that information alone is enough to make a property decision.

The Difference Between Information And Experience

The biggest misconception in property is that the buyer with the most information wins.

In reality, the buyer who interprets the information correctly wins.

AI can help you understand Melbourne property. It can help you research suburbs, compare data and ask better questions.

What it cannot do is replace local experience, inspect a property, negotiate with a selling agent, identify hidden risks or uncover opportunities that aren’t obvious in the numbers.

That is where professional advice still matters. According to the Reserve Bank of Australia, housing remains the largest asset class for most Australian households — which makes the quality of the buying decision even more consequential.

At LP Advisory, we encourage buyers to use AI as a research tool. Just don’t mistake it for a substitute for experience.

Because in Melbourne property, the most expensive mistakes are often made when the answer sounds right but isn’