AI is changing how India searches for homes, but can it go as far as replacing physical property visits? In a candid conversation, Brij Pahwa, Editorial Lead, MartechAI.com and Exchange4Media, speaks with Praveen Sharma, Chief Executive Officer of Housing.com, on the rise of conversational search, predictive discovery, and whether real estate is finally ready for a digital-first future.
Artificial intelligence may be the loudest phrase in technology today, but in real estate, its real impact is likely to be far more practical than theatrical. For Housing.com CEO Praveen Sharma, the biggest shift is not about replacing people overnight or turning property transactions into a fully automated flow. It is about making search smarter, discovery more intuitive, and decision-making far more efficient for the consumer.
In a conversation on the future of proptech, Sharma laid out a view of AI grounded less in hype and more in utility. Real estate, he suggested, is one of the consumer categories where digital infrastructure has already reduced friction meaningfully. A decade ago, buyers would often visit 10, 15 or even 20 homes before making a decision. Today, platforms can help narrow that journey significantly by moving research online and equipping users with enough information to shortlist far fewer options before a physical visit.
That shift, he indicated, is only the beginning.
For Sharma, the next major leap in property discovery will come from conversational search. Instead of relying only on rigid filters such as budget, bedroom count or locality, users are likely to search more naturally, describing the kind of home they want in ordinary language. A buyer may increasingly expect to express nuanced requirements in one go, whether that includes location, amenities, layout preferences or surrounding infrastructure. Housing.com, he said, is working toward that experience, though enabling it requires significant groundwork in data, content structuring and search architecture.
That is where AI moves from being a buzzword to being infrastructure.
The company’s view appears to be that better outcomes in real estate discovery will come from a stronger understanding of user intent. Every interaction on a platform- every search, click and browsing action leaves behind a behavioural footprint. Sharma argued that advances in models and compute power now make it much more feasible to process that information at scale and return more personalised results than was possible even a few years ago. In effect, the promise of AI in proptech is not just automation for its own sake, but the ability to map intent better and improve relevance more consistently.
That also has direct implications for marketing and conversion.
In Sharma’s telling, personalisation is not a cosmetic upgrade. It improves conversion because the platform learns more with every interaction and can better understand what the consumer is likely to respond to. In a category as high consideration as housing, that matters. Discovery is rarely linear, and intent is rarely captured by one search session. AI, combined with data science, can help interpret those fragmented signals and make the journey more responsive over time.
Still, Sharma stopped short of positioning AI as magic. On the question of data and India’s diversity, he made a pragmatic point: India may be highly heterogeneous, but that does not make it fundamentally incomparable to other large markets. The key is training models on enough localised data across cities and consumer patterns. In his view, the principles are not uniquely Indian so much as heavily data-dependent. If Mumbai, Delhi and Bengaluru behave differently, the answer is not to abandon modelling, but to train on those differences well.
That view also extends to how Housing.com is thinking about growth beyond the metros. Sharma acknowledged that by volume, tier-one cities still dominate listings and users. But he pointed to stronger growth in tier-two markets and said the company has expanded operations into additional cities to capture that momentum. Smartphone penetration, he suggested, is no longer the limiting factor. The bigger task is to enter markets with enough service capability for local agents, developers and channel partners so that listing depth and platform utility can build sustainably.
If AI can improve discovery, though, it still has to contend with one of real estate’s oldest problems: trust.
Sharma did not deny the trust deficit that continues to shadow the sector. Instead, he framed it as a medium- to long-term problem that must be solved in increments across a large and fragmented ecosystem. One of the clearest examples he pointed to was verified listings. Housing.com is trying to push the ecosystem toward stronger verification by giving verified listings better visibility in search, while also improving consumer understanding of the difference between verified and non-verified inventory. The company, he said, has seen steady growth in verified listings over time and expects that credibility to continue improving over the next two years.
That point is important because AI in real estate will only be as good as the trustworthiness of the underlying information. If search becomes more conversational and recommendations become more predictive, then the quality, freshness and credibility of listings become even more central to the user experience.
Another area Sharma identified as both highly visible and still unresolved is price discovery. In more developed markets, real estate platforms often play a much larger role in helping consumers understand the likely value of a property. India, he suggested, is still some distance away from that level of precision. Too many variables influence actual pricing, and transaction values are not always easily discoverable in a structured way. Digitisation of transactions could help over time, but even that would not automatically make valuation exact. AI may improve relative pricing signals, but precise price discovery remains one of the category’s harder problems.
So what defines the next few years for Housing.com?
Sharma’s answer was not about one big shiny feature. It was about using AI to navigate change productively, improve operational efficiency and, more importantly, solve problems that earlier technology could not. Conversational search is one example. Another is the ability to extract meaning from visual content, such as identifying features from images and tagging listings better so that search becomes richer and more intuitive. That kind of capability, he suggested, is what makes this period exciting. Not because AI will instantly commoditise everything, but because companies that move faster can create an advantage before those capabilities become standard across the market.
On the broader question of whether property buying and selling can become fully digital, Sharma’s answer was measured. Renting, he believes, could reach that stage much sooner because the financial stakes are lower. Buying is likely to take longer, simply because a home is one of the biggest cheques a person writes in their lifetime. But he does see a future in which almost every part of the journey becomes digital, with only the final checkpoint remaining physical.
That may be the clearest takeaway from Housing.com’s AI vision. The future of proptech is not necessarily a world where technology removes every human touchpoint. It is a world where the digital layer becomes intelligent enough to reduce uncertainty, sharpen intent, improve trust and make the eventual decision far more informed than it is today.
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