Closing Smarter: AI helps developers lift home sales by 20%

Developers are using AI across the board — from customer-facing platforms to backend operations — to refine every aspect of the value chain

Artificial intelligence (AI) is helping Indian real estate firms increase home sales conversion rates by as much as 20 percent as developers lean into technology to streamline customer experiences, optimise pricing and speed up decision-making. In metropolitan and Tier-I cities, dynamic pricing powered by AI is gradually replacing static rate cards, enabling developers to react to market trends in real time and close deals faster.

“From our conversations with sector experts, the most immediate impact of AI is visible in sales, marketing and pricing strategies," said Shekhar Patel, president of the Confederation of Real Estate Developers' Associations of India (CREDAI). "AI-powered chatbots, virtual site walkthroughs and predictive customer analytics are helping developers personalise offerings and improve conversion rates by up to 20 percent.”

Developers are using AI across the board—from customer-facing platforms to backend operations—to refine every aspect of the value chain.

Tata Realty and Infrastructure has implemented AI tools like Salesforce Marketing Cloud and Einstein AI to enhance homebuyer engagement and reduce friction across digital touchpoints. These tools have allowed the company to personalise interactions and optimise lead qualification in real time.

“Since implementing AI-led tools, we have achieved a 20 percent reduction in CPQL (cost per qualified lead), and booking conversions rate have grown by 10 percent year-on-year,” said Sanjay Dutt, MD and CEO of Tata Realty. “The improvements stem from sharper targeting, real-time campaign optimisation and improved homebuyer interactions.”

At the Ahmedabad-based Ganesh Housing Corporation, AI is being deployed not only in customer service and lead qualification but also throughout the project lifecycle—from visualisation and planning to risk identification and post-handover operations. “Earlier, our projects used to take four to five years to complete. Now, with AI and new construction technologies like precast, we’re delivering projects in as little as 18 months,” said Viren Mehta, president, Ganesh Housing. “AI enables faster decision-making, better planning and risk mitigation.”

Along similar lines, Saurabh Runwal, director, Runwal Realty, a Mumbai-based builder, said the company is using AI-generated visuals and immersive virtual walkthroughs to help clients visualise unbuilt spaces. "On the backend, AI is helping us go beyond visuals, analysing site constraints, predicting material needs and even flagging design efficiencies, helping shave 10–15 percent off the planning time in some cases," he said.

In the case of TRG Group, a Noida, Uttar Pradesh-based developer, predictive lead scoring tools have improved the quality of leads while virtual tours have reduced physical visits by over 30 percent. Automation of follow-ups and AI-driven CRM tools have cut the sales cycle by nearly a fifth. “These quantifiable results reflect the strategic significance of AI in automating sales processes and enabling a superior customer experience,” said Jitendra Goyal, director, channel sales at TRG Group.

ElitePro Infra, too, is seeing marked improvements. Their AI-driven CRM now ranks leads in real time, and virtual tours have become especially useful for expatriate Indians and remote buyers. “AI has improved the quality of leads, especially those collected through internet campaigns,” said Viren Mehta, founder and director of the Gurugram, Haryana-based company. “Virtual tours have minimised wasteful visits to sites, and personalised interaction has increased buyer confidence and decreased decision latencies.”

The impact is being felt beyond sales. AI is assisting developers with construction planning, cost estimation and timeline accuracy. Smart building systems powered by AI are also enhancing post-handover experiences in commercial spaces by managing utilities, personalising amenities and tracking usage patterns.

Building in-house versus external collaborations

Developers are mostly adopting a hybrid model when it comes to building AI capabilities, tapping internal talent while also being open to external partnerships. “Our hybrid approach to AI deployment combines the use of in-house capabilities with proptech products,” said Goyal. “Solutions like LeadSquared, Square Yards Tech and MagicBricks AI Solutions have been most effective for us in enhancing our digital strength.”

Tata Realty follows a blended model too. “We leverage Salesforce along with select implementation partners. For AI-related capabilities, we primarily collaborate with verified IT vendors to ensure robust data privacy and security,” said Dutt. “For virtual tour and metaverse integrations, we engage with innovative proptech startups.”

Ganesh Housing works closely with consultants and external partners, especially under the Gujarat IT and GCC policies. “We even created a comparison tool that shows companies their savings if they expand into Gujarat versus cities like Bangalore or Hyderabad,” said Mehta. “It’s part of our broader shift toward a more service-oriented real estate model.”

On the other side of the aisle, proptech consultancies like Bric X Infra have also seen traction in AI collaborations. “The majority of the solutions we implement are in collaboration with private proptech platforms,” said Bric X founder Amit Rangi. “The Indian ecosystem is well saturated with startups providing custom solutions. But still, it is challenging to integrate those with legacy systems and even to retain talent that can switch between tech and real estate with ease.”

Common challenges to AI adoption

Despite the opportunities, developers acknowledge that several hurdles remain. Integrating AI with existing systems, managing unorganised data and attracting people with the necessary skills are recurring issues. “There are challenges like unstructured data, integration of existing systems and shortage of talent with AI skills in real estate,” said Goyal.

Patel of CREDAI echoed this sentiment, citing a study by the IT industry body. “A NASSCOM report highlights that 60 percent of Indian enterprises face AI-related skill shortages, and this is no different for real estate,” he said. “Regulatory frameworks in India are catching up, but there’s a need for clearer policies around AI in real estate, particularly in pricing, digital transactions and valuations.”

As AI becomes more embedded in the sector, developers are careful to strike a balance between automation and the human touch. “We see AI as a complement to human interaction, not a replacement,” said Dutt. “The human element—especially in high-value real estate transactions—remains critical for building trust and offering nuanced advice.”

What next?

Looking ahead, industry leaders believe AI will continue disrupting how properties are planned, sold and managed. TRG Group is already exploring AI-based safety monitoring and material optimisation on sites. ElitePro Infra is testing dashboards for progress tracking and is evaluating AI-linked BIM or building information modelling tools to cut waste.

Bric X Infra believes the biggest disruption is yet to come. “In the future, we anticipate the largest disruption from AI in real estate to occur in project sales, valuation modelling and construction management,” said Rangi. “Proptech isn’t a buzzword; it’s fast becoming the backbone of real estate today.”