About this episode

Luke Metcalfe discusses the limitations of AI in predicting property market trends and explores the factors that truly drive capital growth.

AI is quickly becoming the go-to tool for property research—but can it actually predict where the market is heading? In this episode, Luke Metcalfe returns to put that assumption to the test, analysing thousands of suburb predictions across multiple GPT models and real market data. The result is clear: AI doesn’t just struggle to forecast property growth—it often underperforms the market entirely. We unpack why this happens, from the way large language models are trained to the dangerous feedback loop of consensus-driven data. If AI is simply reflecting what’s already popular, are investors just paying a premium to follow the crowd? The conversation also explores the rise of AI-generated property reports, the risks of relying on median data, and why many “data-driven” strategies may not be as objective as they seem. Beyond the critique, this episode shifts the focus to what actually drives capital growth. From owner-occupier demand and supply constraints to hyper-local, street-level dynamics, Luke shares what the data reveals when you strip away the noise. We also touch on how recent policy changes and shifting incentives could reshape investor behaviour—and why thinking like a…

People in this episode

Host: Chris Bates

Guest: Luke Metcalfe

Topics covered

• AI in property research
• property market predictions
• capital growth drivers
• data-driven strategies
• investor behavior
• property reports

Keywords

• AI
• property growth
• market predictions
• data analysis
• investing
• owner-occupier demand
• supply constraints

Mentioned in this episode

Organizations: GPT

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