AI In The Real Estate Market Size, Share, Opportunities, And Trends By End-Users (Owners, Developers, Engineers and Architects, Investors), By Deployment (Cloud, On-Premise), By Application (Marketing, Automated Valuation Models, Analysis, Personalized customer experience, Design and Planning, Others), And By Geography - Forecasts From 2024 To 2029

The AI in the real estate market is expected to grow at a CAGR of 11.52%, reaching a market size of US$754.899 million in 2029 from US$467.042 million in 2024.

AI in Real Estate means using technology and algorithms in activities like searching for a property, analyzing investments, managing properties, serving customers, and promoting the business. These help to enhance processes, ease decision-making, enhance service delivery, and exploit a property. The search and recommendation system, predictive analytics, and AVM systems are some of the components of AI in real estate. AI systems analyze large pools of real estate data and provide property recommendations to buyers, renters, and real estate investors.

AI systems use different machine learning algorithms to analyze tendencies in the real estate markets, price changes of properties, and potential rents to help investors maximize the use of their rentiers’ assets. AVMs use attributes of properties, information about the markets, and other deals that have occurred before to come up with the property value.

What are AI in the real estate market drivers?

• Increasing demand for personalization is contributing to AI in the real estate market growth

AI systems can conduct and analyze a lot of information, create personal property recommendations, give investment forecasts, and manage customers. Among the various solutions available on the market, Blackshark.ai Roof, an AI-powered brokerage assistant, can assist emerging enterprises in generating new real estate leads and analyzing customers more effectively for potential sales opportunities. This service aims to reach the right recipients at the right time through upselling and cross-selling strategies.

Both ordinary individuals and investors are driving technology integration in the real estate market. The main goal is to help real estate professionals provide a better experience for buyers, sellers, tenants, and investors through more targeted marketing.

• Smart building technologies are contributing to AI in the real estate market growth

The growth of new technologies, such as the application of Artificial Intelligence and the Internet Of Things (IoT) into smart buildings, gives room for the utilization of AI in Commercial Real Estate. Smart building systems improve energy-saving, provide a good tenant experience, and enhance safety, thus providing an advantage to landlords and tenants.

Among various products, one is ComeHome, a digital platform that improves the homeownership experience by making it easy for clients to research and purchase residential real estate. It enhances point-of-sale and loan origination processes, allowing companies to better engage with customers and streamline housing transactions. The real estate business is using AI to improve customer experience, marketing efficacy, virtual property tours, CRM capabilities, predictive analytics, and operational efficiency, therefore revolutionizing the digital landscape of property management.

• Increased deployment is also contributing to AI in the real estate market growth

AI in the real estate market is segmented based on different deployment models. Cloud-based AI solutions in real estate use internet-based servers to store, process, and analyze data, allowing for scalability, flexibility, and accessibility. They offer real-time data processing, predictive analytics, collaboration features, and resource and service pricing based on subscriptions.

Moreover, On-premise AI solutions, which are implemented directly within an organization's infrastructure, offer improved data protection, privacy, and customization, making them the preferable choice for real estate enterprises with rigorous regulatory constraints, sensitive data, or particular integration requirements.

Major challenges hindering AI in the real estate market:

• Complexity of real estate processes hamper the market growth

Real estate transactions require complicated procedures and legal issues. Creating AI systems that can successfully explore and comprehend these intricacies is a problem. Moreover, during the forecast period, the market is also projected to be restrained by cybersecurity concerns and inadequate technical skills. Real estate businesses are still reluctant to adopt the technology due to fears of data safety and privacy.

Geographical outlook of AI in the real estate market

• North America is witnessing exponential growth during the forecast period

North America, particularly Silicon Valley, is a hotbed of technical innovation, with major AI firms and startups such as HouseCanary, Zillow, Redfin, and Trulia pushing advances in AI technology for a variety of sectors, including real estate. The North American real estate organizations were among the first to use AI and machine learning technology to improve numerous parts of their operations, including property appraisal, predictive analytics, market analysis, client interaction, and property management. Overall, North America's technological strength and active real estate market make it a crucial participant in adopting and developing artificial intelligence in this industry.

Key launches in AI in the real estate market

• In December 2023, Redfin released Redesign, an AI-powered application that allowed users to modify the appearance of walls, floors, and worktops in home photos. The Roomvo-powered program allowed you to see life situations, identify acceptable houses, and experiment with various design concepts.
• In July 2023, Roof AI and Percy, a real estate data and analytics leader, collaborated to improve this market's customer experience and income streams. The agreement would combine their cutting-edge technology to provide real estate brokers and agents with a holistic solution for increased income streams and improved client experience.

The AI in the real estate market is segmented and analyzed as follows:

• By End-Users
  • Owners
  • Developers
  • Engineers and Architects
  • Investors
• By Deployment
  • Cloud
  • On-Premise
• By Application
  • Marketing
  • Automated Valuation Models
  • Analysis
  • Personalized customer experience
  • Design and Planning
  • Others
• By Geography
  • North America
    • USA
    • Canada
    • Mexico
  • South America
    • Brazil
    • Argentina
    • Others
  • Europe
    • Germany
    • France
    • UK
    • Spain
    • Others
  • Middle East and Africa
    • Saudi Arabia
    • UAE
    • Israel
    • Others
  • Asia Pacific
    • China
    • Japan
    • India
    • South Korea
    • Indonesia
    • Taiwan
    • Others

1. INTRODUCTION

1.1. Market Overview

1.2. Market Definition

1.3. Scope of the Study

1.4. Market Segmentation

1.5. Currency

1.6. Assumptions

1.7. Base and Forecast Years Timeline

1.8. Key Benefits to the Stakeholder

2. RESEARCH METHODOLOGY  

2.1. Research Design

2.2. Research Processes

3. EXECUTIVE SUMMARY

3.1. Key Findings

3.2. CXO Perspective

4. MARKET DYNAMICS

4.1. Market Drivers

4.2. Market Restraints

4.3. Porter’s Five Forces Analysis

4.3.1. Bargaining Power of Suppliers

4.3.2. Bargaining Power of Buyers

4.3.3. Threat of New Entrants

4.3.4. Threat of Substitutes

4.3.5. Competitive Rivalry in the Industry

4.4. Industry Value Chain Analysis

4.5. Analyst View

5. AI IN THE REAL ESTATE MARKET BY END-USERS

5.1. Introduction

5.2. Owners

5.3. Developers

5.4. Engineers and Architects

5.5. Investors

6. AI IN THE REAL ESTATE MARKET BY DEPLOYMENT

6.1. Introduction

6.2. Cloud

6.3. On-Premise

7. AI IN THE REAL ESTATE MARKET BY APPLICATION

7.1. Introduction

7.2. Marketing

7.3. Automated Valuation Models

7.4. Analysis

7.5. Personalized customer experience

7.6. Design and Planning

7.7. Others

8. AI IN THE REAL ESTATE MARKET BY GEOGRAPHY

8.1. Introduction

8.2. North America

8.2.1. By End-User

8.2.2. By Deployment

8.2.3. By Application

8.2.4. By Country

8.2.4.1. USA

8.2.4.2. Canada

8.2.4.3. Mexico

8.3. South America

8.3.1. By End-User

8.3.2. By Deployment

8.3.3. By Application

8.3.4. By Country

8.3.4.1. Brazil

8.3.4.2. Argentina

8.3.4.3. Others

8.4. Europe

8.4.1. By End-User

8.4.2. By Deployment

8.4.3. By Application

8.4.4. By Country

8.4.4.1. Germany

8.4.4.2. France

8.4.4.3. UK

8.4.4.4. Spain

8.4.4.5. Others

8.5. Middle East and Africa

8.5.1. By End-User

8.5.2. By Deployment

8.5.3. By Application

8.5.4. By Country

8.5.4.1. Saudi Arabia

8.5.4.2. UAE

8.5.4.3. Others

8.6. Asia Pacific

8.6.1. By End-User

8.6.2. By Deployment

8.6.3. By Application

8.6.4. By Country

8.6.4.1. China

8.6.4.2. Japan

8.6.4.3. India

8.6.4.4. South Korea

8.6.4.5. Indonesia

8.6.4.6. Taiwan

8.6.4.7. Others

9. COMPETITIVE ENVIRONMENT AND ANALYSIS

9.1. Major Players and Strategy Analysis

9.2. Market Share Analysis

9.3. Mergers, Acquisitions, Agreements, and Collaborations

9.4. Competitive Dashboard

10. COMPANY PROFILES

10.1. HouseCanary

10.2. Zillow

10.3. Redfin

10.4. Trulia

10.5. Entera

10.6. REimagineHome

10.7. Roof

HouseCanary

Zillow

Redfin

Trulia

Entera

REimagineHome

Roof