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Like many other industries, even though the real estate industry is human centric, within the next 5-7 years, it will benefit substantially from the use of AI systems. Given below are some important use cases that will be deployed soon, thereby improving efficiency, timeliness, and customer satisfaction as well as reducing cost and human labor.
Listing Descriptions
AI can seamlessly automate the tedious and time-consuming task of creating the listing descriptions. Using GPTs and LLMs, custom AI applications for real estate can be built, thereby answering questions quickly and generating a property description promptly.
Virtual Property Tour
Using AI and augmented reality (AR), potential buyers can get a realistic view of the property without visiting the site. Indeed, owners and realtors can provide almost three-dimensional virtual tours to the buyers that give a true sense of how the property looks and feels (both on the inside and the outside).
Virtual Staging
Similarly, using AR and AI (particularly Gen AI), virtual staging can digitally decorate and furnish vacant spaces in real estate images and videos. Since bringing in and then removing furniture is very costly, live staging adds substantially to sales costs. This method not only reduces the expenses related to conventional staging but also speeds up decision-making and eases transactions in the real estate industry. Moreover, virtual staging allows pre-booking of viewings, thereby avoiding cluttering of owner’s or realtor's calendar.
Lead Generation
AI helps realtors identify potential leads from various sources, such as social media, landing pages, website visits, and online listings. It also provides recommendations to sellers and realtors regarding their efforts in the most qualified leads, which are more likely to convert into sales.
Property Search
AI can effectively assist in the house search process by enabling buyers to choose a property for purchase by highlighting the best features for a specific price, design, location, etc. Furthermore, AI-powered search engines also provide property recommendations to buyers, which are based on individual preferences, providing personalized results.
Customer Support
AI-powered chatbots and virtual assistants, which use Large Language Models (LLMs) in the backend, are now powering customer service across industries. Seeing the growing potential of AI customer services, many companies are now incorporating AI solutions.
How AI in real estate can bring a paradigm shift towards trust & transparency?
Given below are some use cases where AI will help in improving trust and transparency
Property Management - AI is already enabling businesses to track rent and property listings, tenant applications, lease agreements, maintenance requests, and other essential information. This tracking outcome can assist owners and property managers in identifying tenant preferences, maintenance issues, price trends in certain areas, and seasonal availability. Since AI systems can scan property documents for anomalies such as missing signatures and empty fields, ensuring accuracy and compliance with regulatory standards.
Automating Due Diligence - AI can help in automating due diligence by comparing valuations and identifying discrepancies between documents, lease agreements, loan applications, tax records, and more, thereby improving transparency.
Property Analysis - Conducting the property analysis and future valuation is essential in identifying its true worth and deciding whether to invest in it. This analysis includes calculating the net present value and estimating the potential future value of the property. Some factors that influence the property's value include location, size, condition, age, number of rooms, office space, elevators, etc. Indeed, AI systems can provide substantial decision support in this regard.
Intelligent Data Processing - Acquiring documents in real estate can be a complex and time-consuming task due to inconsistent templates, which complicate extracting and organizing data from different formats. AI simplifies this process by efficiently categorizing and then extracting relevant information from various documents such as offers, lease agreements, and loan papers, and then reconciling them. Such reconciliation improves trust and transparency for all involved parties.
What are the challenges in adoption of AI tools by real estate players?
Given below are a few challenges as to why the real estate industry would take substantial time to be fully integrate AI systems into its current work-flow systems and processes:
- Many inventions need substantial infrastructure improvements and capital infusion, which firms are usually unwilling to spend.
- Need for obtaining return on past investment.
- No urgent need to fix the current process - organizations usually feel that “if it ain’t broke, don’t fix it.”
- Massive resistance to change the current the business model - often, business believe “what got me here will also get me there.”
- Risk aversion - most companies and consumers are usually risk averse and concerned about being blamed if an invention fails to perform adequately.
- Need to retrain workforce - many inventions require the workforce to be retrained or upskilled.
- Consumers take time to adapt - innovations require consumers to adapt appropriately, which is time consuming especially for older people.
What are the ways to deal with privacy and compliance issue when using AI?
To ensure privacy, the approach should prioritize informed and active consent. This means clearly explaining how data will be collected and used, not just now but also in the future. Consent should be obtained dynamically, avoiding automatic agreement to terms and conditions. Furthermore, throughout the process, ensure privacy, and confidentiality, and data lineage are tracked carefully. By implementing strong consent management systems, we will allow individuals to adjust their permissions as needed. This ensures ethical data use, respects individual rights, and builds trust in AI-driven initiatives.
Compliance should be managed by obtaining proper certifications like ISO 27001-2022 and SOC-2 audits. These will ensure that government regulations and other compliance issues are incorporated appropriately (and they do not fall through the cracks).
How do you see the future of AI in Indian real estate?
Unlike some of the advanced economies (e.g., USA), since India does not have legacy systems within its real estate industry, this industry has an opportunity of skipping “one generation of technology” that is now old and slow to adapt. Hence, just like the revolution in the digital payments industry in India, there is likely to be a similar revolution in India’s real estate industry.
