AI in Proptech is Taking Smart Buildings to New Heights — Here's How

By Tinotenda Muradzikwa and Ben Ahrens Published on Apr. 25, 2024

Artificial intelligence, or AI, is now a key player in the proptech industry, enhancing efficiency, transparency, and data-driven decision-making. AI automates property search and evaluation tasks, risk analysis, value assessment, and property management. Additionally, it assists in analyzing large amounts of data, enabling informed decisions.

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Some see proptech as the real estate industry equivalent of its financial services counterpart, fintech. Like fintech, proptech is disrupting traditional workflows that rely heavily on manual processes and spreadsheets, which could be more efficient. Proptech has already changed how the real estate world transacts and will continue to develop a stronger foothold as firms adopt these new digital tools and new technologies emerge.

Understanding the current real estate market

AI applications in the real estate industry can be classified into five main categories:

  1. Assessing the property’s market value
  2. Improving lead generation and marketing
  3. Asset tokenization and risk analysis
  4. Energy data analysis and ESG monitoring
  5. AI products for under-development

While some use cases exhibit market readiness and high-growth market adoption, others are only starting to gain early traction and are worth integrating into a long-term strategy.

Innovative building solutions for assessing a property’s market value

Most tools accurately predict upcoming price changes based on the statistical data available, like HouseCanary, a startup that evaluates the house price now and for the future. AI algorithms can collect market data from various sources, including sales history, transportation networks, schools, and crime rates, to predict future property prices accurately.

In contrast, startups such as GeoPhy, CREX Capital, and Enodo are adopting a longer-term approach by pooling novel data sources to predict the future value of properties. GeoPhy uses thousands of data sources to set the price for commercial properties, shopping centers, and other buildings — it’s used by major enterprises, investors, and lenders.

smart buildings_building construction startups

With a greater focus on real estate investors, CREX Capital is revolutionizing the professional and risk-related financing, brokerage, and decision-making process through its AI-enabled B2B SaaS platform based on real-time market and financial data. The platform goes holistic in commercial real estate financing with three main modules: origination, analysis, and documentation.

Similarly, Enodo analyzes rental data and calculates the value specific amenities could bring to a building. By comparing similar market rentals, realtors can maximize the potential of a target property. They analyze rental data and calculate the value a particular piece of equipment would bring if installed in a building. Therefore, Enodo teaches investors which actions deliver real value and can be derived from market data. Realtors can understand a property's competitiveness and maximize its potential by comparing similar market rents.

Improving lead generation and marketing for smart buildings ventures

Real estate businesses can benefit from improved lead generation and marketing strategies. With the right tools and approaches, they can effectively reach their target audiences, generate more qualified leads, and close more sales.

smart buildings_chatbot_person texting

Zillow is one business that processes multiple data points to differentiate hot leads with serious intentions from curious individuals. Their AI real estate app matches clients with relevant offers by finding the listing type they are searching for. The system tracks the data from previously clicked advertisements, browsing activity on REX portals, and online searches. This solution saves time and offers personalized recommendations, 3D walking tours, and proper resource planning.

Regarding AI, Localize.city leverages this new tech to analyze factors such as sunlight, school ratings, transportation, sound, and parking space to deliver informed recommendations to real estate agents, improving customer reviews and closing more deals. Similarly, through AI, other features such as chatbots are another avenue for enhancing lead generation. Companies like HomeServices of Nebraska, Berkshire Hathaway, and The Keyes have contacted Canadian startup Roof.ai’s chatbot to answer tricky customer questions. Machine learning algorithms analyze behavioral patterns and past interactions; the chatbot nurtures prospects with individualized content, engaging customers and growing conversions.

Asset tokenization and risk analysis

The rise of decentralized finance has led to startups like Jointer exploring asset tokenization in real estate. This innovative approach to investing offers a better alternative to traditional one-time investments by minimizing risk and providing diversification to investors. Jointer augments the return on investment for asset owners by using tokens backed by real estate assets. They have integrated an AI engine into their platform to ensure the highest-quality selections are available to investors. This engine analyzes thousands of real estate items before they appear on the platform to determine the best opportunities and most secure investments.


Want to find out more about risk analysis in Real Estate & Construction? Check outpitches from startups like Dwellwell Analytics during our2022 Silicon Valley Real Estate & Construction November Summit.


Analyzing energy data for innovative building solutions

Buildings account for up to 40% of global emissions, making energy efficiency and sustainability vital for companies. AI is helping companies transform these issues by tracking, analyzing, and reducing emissions in buildings. Dr. Andreas Köttl, CEO of Value One, sat down with us to discuss the future of sustainable construction and emphasized the importance of real estate developers being driven by ESG and taxonomy needs. Be sure to check out the full fireside chat below for more in-depth insights.

When looking at startups in this space, Gridium is leading this effort by analyzing energy data, specifically by processing data from smart energy meters, fluctuating utility rates, and weather changes. This information can identify the highest-demand charges and moments of energy wastage, providing companies with data-driven insights to reduce energy consumption.

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Smart parking based on AI technology is an innovative solution that harnesses data from sensors and cameras, building an AI-driven parking management system. Such devices are embedded near parking lots to detect parking space availability. Intelligent parking solutions reduce fuel consumption by cutting drivers' searching time and reducing search traffic caused by nearly a third of urban area traffic created by drivers looking for a parking spot. Besides helping drivers locate parking spots, IoT in parking allows businesses to fill more parking spots and advertise their services across various apps and websites. They also reduce carbon emissions associated with drivers' driving around searching for parking spaces.

AI for construction startups working with properties under development

DeepBlocks utilizes AI in commercial real estate by creating 3D models of properties under development. Customers can set their parameters and receive a 3D image and a comprehensive financial analysis of their project. As a result, the company automates the calculations and simplifies communication between many stakeholders.

Meanwhile, Doxel employs AI to track installed items on building sites and automatically measures earned value for each item. Customers can visualize construction sites in 3D, monitor progress and completion stats, and detect installation errors.

Opinion on AI in proptech


By Alfredo Gomez, Senior Partnerships Manager for Plug and Play Fintech

AI is expected to improve the efficiency and effectiveness in various aspects of the real estate industry.

One potential use is in predictive maintenance, where machine learning algorithms can identify potential issues with buildings and predict when care is needed, reducing costs and increasing efficiency. Another possible use case is smart home automation, where AI can be used to automate various aspects of the home, from temperature and lighting to security and entertainment.

NEXT: Tokenization of Real Estate: Liquidity and Security

AI can also be used in property valuation, which can help provide more accurate and timely assessments of property values.Some startups already use AI-powered chatbots to improve customer service and support for buyers and sellers, streamlining the buying and selling process. Overall, the future of AI in proptech is bright, and we’re likely to see many more use cases emerge as the technology continues to evolve and mature.


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