This week’s India AI Impact Summit delivered a clear message: artificial intelligence is moving beyond being a showcase technology and is fast becoming critical national infrastructure. The shift—from laboratory experiments to real-world outcomes—is particularly significant for the real estate sector, where decisions are high-value, emotionally charged, and heavily dependent on trust and compliance.
Over the past decade, the property industry focused largely on digitising its surface layer. Online listings, lead management systems, customer relationship platforms and performance dashboards improved visibility and efficiency. The first wave of AI then strengthened enterprise automation, enabling faster document processing, smarter customer support and automated follow-ups. These developments have helped reduce cost-to-serve, shorten turnaround times and bring greater operational consistency.
However, industry experts say the next phase will be defined by what is increasingly being called “decision intelligence”.
Unlike basic chatbots, decision intelligence combines large datasets, contextual reasoning and risk signals to support human decision-making under uncertainty. In real estate, uncertainty is widespread. Price discovery remains uneven, inventory is fragmented, demand patterns shift quickly and transaction processes differ across states, developers and asset classes. This often leads to delays, misinformation and a reliance on informal networks of trust.
Decision intelligence aims to address these gaps by answering more complex, high-value questions. These include determining a property’s fair market price using comparable sales and micro-market trends, assessing the probability of a deal closing based on documentation readiness and financing risk, and flagging hidden legal or compliance issues. It can also recommend the most effective next action—whether that is scheduling another site visit, adjusting an offer or triggering approvals.
In practical terms, the transition marks a move from automating routine tasks to engineering measurable outcomes. Industry observers say the most advanced real estate organisations will increasingly treat AI as an operating system—one that captures buyer intent accurately, continuously verifies supply, maintains auditable decision trails and improves recommendations through feedback from real transactions.
