Property Tech
Property decisions leap from location to logic
AI is changing the emotions and instincts behind the way property is bought, writes ANTONIE GOOSEN, founder and principal of Meridian Realty.
Once driven by instinct and reputation, property is becoming an information-led, algorithm-assisted decision environment, and it will feel very familiar to anyone in tech. For decades, property decisions were guided by instinct, reputation and one simple rule: location, location, location. I’ve worked in residential property long enough to see how powerful that principle once was. But today, it’s no longer enough.
As data becomes more accessible and artificial intelligence begins influencing everyday decision-making, property is undergoing a shift the technology sector will recognise immediately. The industry is moving from intuition-led judgement to information-driven, AI-assisted decision intelligence. Location still matters, but it no longer tells the whole story. Increasingly, data and algorithms determine how location is interpreted, priced and de-risked.
Property enters the AI era
Residential property is now following the same transformation path already seen in finance, logistics and retail. Modern buyers arrive with access to information that was previously locked behind banks, valuers or industry insiders: comparable sales, pricing histories, municipal data, infrastructure plans and even satellite imagery. What’s changed is how that information is processed. AI systems are starting to connect these data points at scale, identifying relationships and patterns humans struggle to detect consistently. This isn’t about replacing people. It’s about augmenting judgement. In much the same way AI supports fraud detection in fintech or demand forecasting in supply chains, it helps surface risk, mispricing and emerging pressure points in property markets.
From hindsight to probability
Historically, property analysis has been backward-looking. We analysed what sold, when it sold and at what price. AI enables a shift from hindsight to probability. Instead of relying solely on past performance, buyers and sellers can now model forward, testing potential scenarios. These models can incorporate infrastructure investment, semigration trends, supply constraints, interest-rate sensitivity and behavioural patterns. This mirrors how AI is already used in credit scoring and decision-intelligence platforms. The goal isn’t certainty. It’s better probability and more informed trade-offs.
Less emotion, more confidence
Property will always be emotional. Homes are personal, and decisions are rarely purely rational. What’s changing is how emotion is balanced against evidence. Buyers are becoming more confident walking away when the numbers don’t make sense. Data provides a counterweight to impulse, much like risk models do in enterprise decision-making. When intelligent analysis supports information, decisions become more disciplined and consistent. Confidence improves not because risk disappears, but because it’s better understood.
The agent as “human in the loop”
As AI becomes more embedded in property decisions, the role of the estate agent isn’t disappearing. It’s evolving. AI can surface patterns, correlations and red flags, but it can’t fully understand human priorities, lifestyle trade-offs or contextual nuance. That’s where the agent remains essential. In AI terms, the modern agent increasingly operates as a “human in the loop”. The role is to interpret, validate and sometimes challenge what the data suggests. AI informs decisions, but people still make them.
Transparency at machine speed
AI also accelerates transparency. Pricing anomalies stand out quickly. Over-inflated listings become obvious when benchmarked against AI-enhanced market data. The result is faster feedback loops and greater accountability. Sellers who price realistically and disclose accurately tend to transact more quickly. Buyers engage with greater confidence. AI doesn’t tolerate ambiguity, and neither do data-literate consumers.
A familiar shift for tech leaders
For anyone in IT or technology leadership, this evolution should feel familiar. What we’re seeing is a traditional industry becoming data-native. Location still sets the baseline, but information and AI increasingly determine the outcome. As artificial intelligence embeds itself deeper into decision-making across sectors, property is no longer an outlier. It’s simply catching up.
