MIDDAY EXPLAINS: AI simplifies decision-making in real estate operations, here’s how

In just a short span, Artificial Intelligence (AI) has permeated various facets of the real estate ecosystem. From property valuation and market analysis to customer interactions and property management, AI's influence on the realty domain is pervasive.

As AI advances rapidly, experts hint that its role in reshaping the real estate landscape is only set to deepen. "Both buyers and sellers are benefiting," remarks Sandeep Ahuja, CEO of Atmosphere Living: A Bandra-based realty service that works to transform luxury living with customised end-to-end amenities.

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In a bid to investigate how AI is ushering in a new era of innovation in real estate operations, we dialled up Mumbai-based experts, who uncover the myriad ways AI has revolutionised this sector.

How businesses leverage AI in the realm of real estate

A growing number of architects are now using AI in their daily operations to streamline space planning and design. Meanwhile, in customer-facing sectors of the realty business, Govind Rai, CEO and co-founder of Andheri-based real estate marketing and data analytics group - Insomniacs Digital, discusses AI's growing presence in his field of work:

Automation in communication: This encompasses everything from crafting creatives to implementing intelligent workflow automation tailored as per various customer personas based on factors like location, inquiry timing, family size and preferred language.

Virtual experiences: Creating virtual experiences for customers in the virtual reality world and developing digital twins for cities or projects.

Predictive customer transaction analysis: Predicting the likelihood of customer transactions with properties through iterative analysis of their interactions at different touchpoints.

Real-time call centre assistance: Supporting call centre teams with real-time customer interactions by providing guidance for accurate responses and implementing triggers for prompt and relevant answers.

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Ahuja stresses that investor empowerment will always be the first thing to mention when talking about the impact caused by AI in real estate. When investors are empowered with the knowledge of diverse opportunities available to them in every aspect of real estate investment, that too in real time, the buyer's side of the value chain is forced to upgrade as well.

When buyers are more empowered, they are more aware of the offerings that the market is truly offering to them, not just in terms of returns from an investment, but also crucial details extracted from mountains of documentation that could be highly tedious for buyers. "I think it's safe to say that the decision-making being simplified on all sides of the value chain has been one of the primary ways in which AI is transforming the segment," he adds.

Lucy Roychoudhury, CEO of Runwal Bliss, a prominent real estate developer in Mumbai specialising in residential, commercial, and organised properties, emphasises that AI is changing the industry at a lightning pace. From personalised property searches to recommendations, AI has significantly enhanced the homebuyer's experience. Moreover, AI's applications extend beyond customer-facing interactions, proving invaluable in studying business analytics.

Role of AI in shaping Mumbai‘s estate market
Commenting on how AI has been an integral factor in the execution of various real estate projects in Mumbai, Roychoudhury remarks that AI has helped in developing an understanding of market trends, price dynamics and demand patterns in different micro markets within the metropolitan.

"It has been useful in figuring out the impact of infrastructure development on demand, shifting consumer preferences, locations in demand, etc. Take, for instance, the growing demand in hotspots like Kanjurmarg, Dombivli, Navi Mumbai and other burgeoning areas, which AI can analyse to facilitate well-informed choices," she outlines.

Ahuja reveals that in addition to the data analysis and investor empowerment brought about by AI, it has also played a huge role in the sheer luxury offered to buyers. The resultant effect is that the luxury real estate market of Mumbai now offers a lifestyle that might have been unimaginable just a decade ago. Sophisticated smart home systems connecting exquisite physical luxuries are one example of its application.

When it comes to Mumbai's real estate sector, Rai points out that AI and Big Data play crucial roles in optimising property valuation and investment strategies by analysing vast data sets that include past transaction data, current market conditions, regulatory changes and consumer behaviour trends. For instance, tools like predictive analytics can model property valuations under different market scenarios, thus aiding in investment decisions.
With this kind of knowledge available at the fingertips, decision-making processes are enhanced in all directions. "This enhanced investor persona in the real estate market is going to be the reason behind the real tech industry's boom in the coming years. We envision that anyone who is in the network of value within the real estate industry will soon have options of apps and user interfaces to choose from, for both individual entrepreneurs as well as enterprise clients," predicts Ahuja.

(L-R) Govind Rai, Lucy Roychoudhary, Mr. Sandeep Ahuja

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It's algorithmic
Rai shares how AI algorithms analyse market trends and patterns to help businesses make informed real estate decisions. "By studying historical data points around supply and demand, developers are now gaining an edge by making a sound choice around what configuration would be the best fit for particular land parcels."

For instance, algorithms prove invaluable in projecting profit and loss (P&L) estimates for a specific land parcel, comparing it against data from the Forest Survey of India regarding consumption and considering the planned mixed configuration.

Additionally, AI algorithms have made it possible for businesses to "co-pilot" real estate development projects from start to end, highlights Ahuja. "Some of these possibilities opened to us in the sector thanks to innovations in space optimisation and schedule generation." These solutions offered by AI to the real estate segment today allow businesses to automate large parts of their processes, thereby enhancing efficiency in previously time-consuming tasks such as tenant request management, and lease negotiation.

Limitations of AI in real estate
Till the time all the data sets are analysed right, with proper attribution given to the variance, there's no real threat in terms of leveraging AI models, stresses Rai. However, he admits that projections regarding profit and loss (P&L) could be inaccurate if a location has historically experienced a high volume of cash transactions and the appropriate benchmarks are not considered. In such cases, the model might generate entirely erroneous forecasts for those areas and projects.

He suggests that in order to develop an effective media mix, the technology employed across the entire ecosystem must be robust enough to capture accurate data and attribution at every stage. Excessive manual intervention at multiple stages can lead to significant deviations in predictions.
On the other hand, Roychoudhury highlights that one possible challenge with AI could be rapid evolution. This will require constant correction in integration methods and evaluating the output accordingly.

She continues, "another critical aspect of real estate, especially with home buying, has been the emotional involvement with the purchase. Home buying has always been one of the biggest investments anyone ever makes and this is something that developers need to keep in mind. With its digital power, AI analyses projects, location, price, supply, etc factually with hard numbers but without the involvement of any human emotion."

While this is beneficial in terms of analysing data, emotions linked with a purchase decision will also have to be factored in separately to arrive at a holistic conclusion, she adds.

To conclude, Ahuja remarks that real estate players must know their limitations as a business that is part of a larger community. "There are numerous aspects of real estate that remain difficult to quantify, and more harder still, collect data for. This factor, in combination with the rapid flux that Mumbai as a city is always in, can make it challenging to rely on data to make predictions too far ahead in the future."

However, with the evolution of the city, the real estate sector is also moving towards more formalisation and more structure at a rapid rate, he informs. Thus, it wouldn't be wrong to be highly optimistic that India's real estate market and India's AI adoption could peak simultaneously, leading to a boom that has rarely been witnessed before in real estate.

Effective tools for AI in real estate

Several AI tools have proven effectivein Rai's experience, such as predictive analytics platforms and AI-driven CRM systems that offer insights into consumer behavior and sales trends. Tools like Chat-GPT and Google Gemini aid in powering multiple solutions today for real-time decision-making by providing predictive analytics and customer engagement insights, which have significantly boosted operational efficiency and customer satisfaction.

Accuracy data used in AI-driven decision-making processes

Real estate professionals ensure the accuracy and reliability of data by integrating AI with robust data governance frameworks. This involves regular audits, using reliable data sources, and cross-validating AI outputs with market trends and historical data. By centralizing data through an enterprise AI that aggregates and cleans data from multiple sources, the risk of inaccuracies diminishes significantly.

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