Gurgaon Homebuyer Awarded Rs 27 Lakh Compensation: How AI Transformed Real Estate Valuations

The Haryana Real Estate Regulatory Authority (HRERA) in Gurgaon has awarded a significant compensation of nearly Rs 27 lakh to a homebuyer after his allotment in ‘The Heartsong’ project was cancelled due to a lack of payments. In a pioneering move, the adjudicating officer used artificial intelligence (AI) to calculate real estate market trends, ensuring a fair and data-driven decision.

This is the second such case where the authority and the same officer have utilized AI. Earlier this year, HRERA ordered a payout of over Rs 4 crore to a Chintels Paradiso flat buyer using a similar method.

In the latest judgment announced on May 6, HRERA Adjudicating Officer Rajender Kumar directed Experion Developers Pvt. Ltd. to pay Rs 26,96,000 as compensation to the complainant, Mukesh Sharma. The authority also awarded Rs 1 lakh for mental agony and Rs 50,000 towards litigation expenses.

Mukesh Sharma had applied for a residential apartment in ‘The Heartsong’ project in Sector 108 off the upper Dwarka expressway in November 2012. Despite paying Rs 20,73,670 against a total sale consideration of Rs 82,95,076 by July 2016, the developer failed to hand over possession within the stipulated three-year period.

While HRERA had previously passed an order in 2023 directing the developer to refund Sharma’s principal amount with interest, an order that is currently under appeal, the present complaint was filed to seek compensation for mental agony and the loss of property appreciation.

During the hearings, Sharma argued that he suffered massive financial losses because if he had invested his money in another project, it would have appreciated at least three times. However, the authority noted that no reliable evidence had been adduced by the complainant to establish this steep hike in Gurgaon’s property rates.

Noting that the “Forum is legally obliged to adjudge the amount of compensation, keeping in view the facts of the case and prevailing circumstances,” the adjudicating officer turned to artificial intelligence to gauge the real estate market’s trajectory. Quoting the search results verbatim, the judgment noted: “According to AI overview, the residential property prices in Sector 108, Gurugram (along with the Dwarka Expressway) experienced significant appreciation between July 2016 (last payment by complainant) and early 2023 (order of refund), largely driven by the operationalisation of the expressway and improved connectivity.”

The order highlighted further data from the AI prompt, observing that “flat prices grew by over 130% in the last 5 years.” Relying on this 130% growth metric, the authority calculated that Sharma’s paid amount of Rs 20,73,670 would have appreciated to Rs 26,95,771 had it been invested elsewhere. Rounding off the figure, the RERA court ordered a total compensation of Rs 26,96,000 to be paid by the developer. The builder has also been directed to pay this amount with an 11% annual interest from the date of the order until realisation.

In March, Adjudicating Officer Kumar had adjudicated on a case involving the structurally unsafe Chintels Paradiso project in Sector 109, Gurgaon. In that case, the RERA adjudicating officer rejected a government committee’s fixed compensation rate of Rs 7,500 per sq ft for a homebuyer whose flat was deemed unfit for habitation. To establish current market realities, the judge similarly invoked a Google ‘AI overview,’ which showed a massive jump in local property rates between February 2022 and March 2026.

Taking the AI-backed market trends into account, the authority had recalculated the flat’s value at Rs 13,000 per sq ft and ordered the developer, Chintels India Private Limited, to pay Rs 4.16 crore to the homebuyer.

These cases highlight the innovative use of AI in the real estate sector, ensuring fair and accurate compensation for homebuyers while also setting a precedent for future cases. The use of AI tools not only speeds up the decision-making process but also provides a transparent and data-driven approach to calculating compensation, benefiting both homebuyers and developers alike.