by The global generative AI in real estate market size accounted for US$ 351.9 mn in 2022 and is projected to reach around USD 1,047 mn by 2032, growing at a CAGR of 11.52% from 2023 to 2032.
Key Takeaways:
- North America contributed more than 41% of revenue share in 2022.
- By component, the services segment shows a leading growth in the generative AI in real estate market.
- By deployment mode, the cloud-based segment generated more than 60% of the revenue share in 2022.
- By application, property valuation is the dominating segment in the generative AI in real estate market during the forecast period.
- By end-user, the real estate agents segment shares the maximum CAGR during the projection period.
Report Summary
The global generative AI in real estate market report provides a Point-by-Point and In-Depth analysis of global market size, regional and country-level market size, market share, segmentation market growth, competitive landscape, sales analysis, opportunities analysis, strategic market growth analysis, the impact of domestic and global market key players, value chain optimization, trade regulations, recent developments, product launches, area marketplace expanding, and technological innovations.
The study offers a comprehensive analysis on diverse features, including production capacities, demand, product developments, revenue generation, and sales in the generative AI in real estate market across the globe.
A comprehensive estimate on the generative AI in real estate market has been provided through an optimistic scenario as well as a conservative scenario, taking into account the sales of generative AI in real estate during the forecast period. Price point comparison by region with global average price is also considered in the study.
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Generative AI in Real Estate Market Report Scope
| Report Coverage | Details |
| Market Size in 2023 | USD 392.44 Million |
| Market Size by 2032 | USD 1,047 Million |
| Growth Rate from 2023 to 2032 | CAGR of 11.52% |
| Largest Market | North America |
| Base Year | 2022 |
| Forecast Period | 2023 To 2032 |
| Segments Covered | By Component, By Deployment Mode, By Applications, and By End-User |
| Regions Covered | North America, Europe, Asia-Pacific, Latin America, and Middle East & Africa |
Key Highlights:
Reports Coverage: It incorporates key market sections, key makers secured, the extent of items offered in the years considered, worldwide containerized generative AI in real estate market and study goals. Moreover, it contacts the division study gave in the report based on the sort of item and applications.
Market Outline: This area stresses the key investigations, market development rate, serious scene, market drivers, patterns, and issues notwithstanding the naturally visible pointers.
Market Production by Region: The report conveys information identified with import and fare, income, creation, and key players of every single local market contemplated are canvassed right now.
Also Read: Generative Ai In Automotive Market Size To Cross USD 2,691.92 Mn By 2032
Generative AI in Real Estate Market Players
The report includes the profiles of key generative AI in real estate market companies along with their SWOT analysis and market strategies. In addition, the report focuses on leading industry players with information such as company profiles, components and services offered, financial information, key development in past five years.
Major companies operating in this area
- Autodesk
- OpenAI
- Gridics
- Cherry
- HqO
- ai
- Io
- Matterport
- Archistar
Market Segmentation
By Component
- Software Tools
- Services
- Platforms
By Deployment Mode
- Cloud-based
- On-premise
By Applications
- Property Valuation
- Building Design
- Predictive Maintenance
- Energy Management
By End-User
- Real Estate Agents
- Property Managers
- Architects
- Engineers
Regional Segmentation
- North America (U.S., Canada, Mexico)
- Europe (Germany, France, U.K., Italy, Spain, Rest of Europe)
- Asia-Pacific (China, Japan, India, Southeast Asia and Rest of APAC)
- Latin America (Brazil and Rest of Latin America)
- Middle East and Africa (GCC, North Africa, South Africa, Rest of MEA)
Research Methodology
Secondary Research
It involves company databases such as Hoover’s: This assists us to recognize financial information, the structure of the market participants and industry’s competitive landscape.
The secondary research sources referred in the process are as follows:
- Governmental bodies, and organizations creating economic policies
- National and international social welfare institutions
- Company websites, financial reports and SEC filings, broker and investor reports
- Related patent and regulatory databases
- Statistical databases and market reports
- Corporate Presentations, news, press release, and specification sheet of Manufacturers
Primary Research
Primary research includes face-to-face interviews, online surveys, and telephonic interviews.
- Means of primary research: Email interactions, telephonic discussions and Questionnaire-based research etc.
- In order to validate our research findings and analysis, we conduct primary interviews of key industry participants. Insights from primary respondents help in validating the secondary research findings. It also develops Research Team’s expertise and market understanding.
TABLE OF CONTENT
Chapter 1. Introduction
1.1. Research Objective
1.2. Scope of the Study
1.3. Definition
Chapter 2. Research Methodology (Premium Insights)
2.1. Research Approach
2.2. Data Sources
2.3. Assumptions & Limitations
Chapter 3. Executive Summary
3.1. Market Snapshot
Chapter 4. Market Variables and Scope
4.1. Introduction
4.2. Market Classification and Scope
4.3. Industry Value Chain Analysis
4.3.1. Raw Material Procurement Analysis
4.3.2. Sales and Distribution Channel Analysis
4.3.3. Downstream Buyer Analysis
Chapter 5. COVID 19 Impact on Generative AI in Real Estate Market
5.1. COVID-19 Landscape: Generative AI in Real Estate Industry Impact
5.2. COVID 19 – Impact Assessment for the Industry
5.3. COVID 19 Impact: Global Major Government Policy
5.4. Market Trends and Opportunities in the COVID-19 Landscape
Chapter 6. Market Dynamics Analysis and Trends
6.1. Market Dynamics
6.1.1. Market Drivers
6.1.2. Market Restraints
6.1.3. Market Opportunities
6.2. Porter’s Five Forces Analysis
6.2.1. Bargaining power of suppliers
6.2.2. Bargaining power of buyers
6.2.3. Threat of substitute
6.2.4. Threat of new entrants
6.2.5. Degree of competition
Chapter 7. Competitive Landscape
7.1.1. Company Market Share/Positioning Analysis
7.1.2. Key Strategies Adopted by Players
7.1.3. Vendor Landscape
7.1.3.1. List of Suppliers
7.1.3.2. List of Buyers
Chapter 8. Global Generative AI in Real Estate Market, By Component
8.1. Generative AI in Real Estate Market, by Component, 2023-2032
8.1.1. Software Tools
8.1.1.1. Market Revenue and Forecast (2020-2032)
8.1.2. Services
8.1.2.1. Market Revenue and Forecast (2020-2032)
8.1.3. Platforms
8.1.3.1. Market Revenue and Forecast (2020-2032)
Chapter 9. Global Generative AI in Real Estate Market, By Deployment Mode
9.1. Generative AI in Real Estate Market, by Deployment Mode, 2023-2032
9.1.1. Cloud-based
9.1.1.1. Market Revenue and Forecast (2020-2032)
9.1.2. On-premise
9.1.2.1. Market Revenue and Forecast (2020-2032)
Chapter 10. Global Generative AI in Real Estate Market, By Applications
10.1. Generative AI in Real Estate Market, by Applications, 2023-2032
10.1.1. Property Valuation
10.1.1.1. Market Revenue and Forecast (2020-2032)
10.1.2. Building Design
10.1.2.1. Market Revenue and Forecast (2020-2032)
10.1.3. Predictive Maintenance
10.1.3.1. Market Revenue and Forecast (2020-2032)
10.1.4. Energy Management
10.1.4.1. Market Revenue and Forecast (2020-2032)
Chapter 11. Global Generative AI in Real Estate Market, By End-User
11.1. Generative AI in Real Estate Market, by End-User, 2023-2032
11.1.1. Real Estate Agents
11.1.1.1. Market Revenue and Forecast (2020-2032)
11.1.2. Property Managers
11.1.2.1. Market Revenue and Forecast (2020-2032)
11.1.3. Architects
11.1.3.1. Market Revenue and Forecast (2020-2032)
11.1.4. Engineers
11.1.4.1. Market Revenue and Forecast (2020-2032)
Chapter 12. Global Generative AI in Real Estate Market, Regional Estimates and Trend Forecast
12.1. North America
12.1.1. Market Revenue and Forecast, by Component (2020-2032)
12.1.2. Market Revenue and Forecast, by Deployment Mode (2020-2032)
12.1.3. Market Revenue and Forecast, by Applications (2020-2032)
12.1.4. Market Revenue and Forecast, by End-User (2020-2032)
12.1.5. U.S.
12.1.5.1. Market Revenue and Forecast, by Component (2020-2032)
12.1.5.2. Market Revenue and Forecast, by Deployment Mode (2020-2032)
12.1.5.3. Market Revenue and Forecast, by Applications (2020-2032)
12.1.5.4. Market Revenue and Forecast, by End-User (2020-2032)
12.1.6. Rest of North America
12.1.6.1. Market Revenue and Forecast, by Component (2020-2032)
12.1.6.2. Market Revenue and Forecast, by Deployment Mode (2020-2032)
12.1.6.3. Market Revenue and Forecast, by Applications (2020-2032)
12.1.6.4. Market Revenue and Forecast, by End-User (2020-2032)
12.2. Europe
12.2.1. Market Revenue and Forecast, by Component (2020-2032)
12.2.2. Market Revenue and Forecast, by Deployment Mode (2020-2032)
12.2.3. Market Revenue and Forecast, by Applications (2020-2032)
12.2.4. Market Revenue and Forecast, by End-User (2020-2032)
12.2.5. UK
12.2.5.1. Market Revenue and Forecast, by Component (2020-2032)
12.2.5.2. Market Revenue and Forecast, by Deployment Mode (2020-2032)
12.2.5.3. Market Revenue and Forecast, by Applications (2020-2032)
12.2.5.4. Market Revenue and Forecast, by End-User (2020-2032)
12.2.6. Germany
12.2.6.1. Market Revenue and Forecast, by Component (2020-2032)
12.2.6.2. Market Revenue and Forecast, by Deployment Mode (2020-2032)
12.2.6.3. Market Revenue and Forecast, by Applications (2020-2032)
12.2.6.4. Market Revenue and Forecast, by End-User (2020-2032)
12.2.7. France
12.2.7.1. Market Revenue and Forecast, by Component (2020-2032)
12.2.7.2. Market Revenue and Forecast, by Deployment Mode (2020-2032)
12.2.7.3. Market Revenue and Forecast, by Applications (2020-2032)
12.2.7.4. Market Revenue and Forecast, by End-User (2020-2032)
12.2.8. Rest of Europe
12.2.8.1. Market Revenue and Forecast, by Component (2020-2032)
12.2.8.2. Market Revenue and Forecast, by Deployment Mode (2020-2032)
12.2.8.3. Market Revenue and Forecast, by Applications (2020-2032)
12.2.8.4. Market Revenue and Forecast, by End-User (2020-2032)
12.3. APAC
12.3.1. Market Revenue and Forecast, by Component (2020-2032)
12.3.2. Market Revenue and Forecast, by Deployment Mode (2020-2032)
12.3.3. Market Revenue and Forecast, by Applications (2020-2032)
12.3.4. Market Revenue and Forecast, by End-User (2020-2032)
12.3.5. India
12.3.5.1. Market Revenue and Forecast, by Component (2020-2032)
12.3.5.2. Market Revenue and Forecast, by Deployment Mode (2020-2032)
12.3.5.3. Market Revenue and Forecast, by Applications (2020-2032)
12.3.5.4. Market Revenue and Forecast, by End-User (2020-2032)
12.3.6. China
12.3.6.1. Market Revenue and Forecast, by Component (2020-2032)
12.3.6.2. Market Revenue and Forecast, by Deployment Mode (2020-2032)
12.3.6.3. Market Revenue and Forecast, by Applications (2020-2032)
12.3.6.4. Market Revenue and Forecast, by End-User (2020-2032)
12.3.7. Japan
12.3.7.1. Market Revenue and Forecast, by Component (2020-2032)
12.3.7.2. Market Revenue and Forecast, by Deployment Mode (2020-2032)
12.3.7.3. Market Revenue and Forecast, by Applications (2020-2032)
12.3.7.4. Market Revenue and Forecast, by End-User (2020-2032)
12.3.8. Rest of APAC
12.3.8.1. Market Revenue and Forecast, by Component (2020-2032)
12.3.8.2. Market Revenue and Forecast, by Deployment Mode (2020-2032)
12.3.8.3. Market Revenue and Forecast, by Applications (2020-2032)
12.3.8.4. Market Revenue and Forecast, by End-User (2020-2032)
12.4. MEA
12.4.1. Market Revenue and Forecast, by Component (2020-2032)
12.4.2. Market Revenue and Forecast, by Deployment Mode (2020-2032)
12.4.3. Market Revenue and Forecast, by Applications (2020-2032)
12.4.4. Market Revenue and Forecast, by End-User (2020-2032)
12.4.5. GCC
12.4.5.1. Market Revenue and Forecast, by Component (2020-2032)
12.4.5.2. Market Revenue and Forecast, by Deployment Mode (2020-2032)
12.4.5.3. Market Revenue and Forecast, by Applications (2020-2032)
12.4.5.4. Market Revenue and Forecast, by End-User (2020-2032)
12.4.6. North Africa
12.4.6.1. Market Revenue and Forecast, by Component (2020-2032)
12.4.6.2. Market Revenue and Forecast, by Deployment Mode (2020-2032)
12.4.6.3. Market Revenue and Forecast, by Applications (2020-2032)
12.4.6.4. Market Revenue and Forecast, by End-User (2020-2032)
12.4.7. South Africa
12.4.7.1. Market Revenue and Forecast, by Component (2020-2032)
12.4.7.2. Market Revenue and Forecast, by Deployment Mode (2020-2032)
12.4.7.3. Market Revenue and Forecast, by Applications (2020-2032)
12.4.7.4. Market Revenue and Forecast, by End-User (2020-2032)
12.4.8. Rest of MEA
12.4.8.1. Market Revenue and Forecast, by Component (2020-2032)
12.4.8.2. Market Revenue and Forecast, by Deployment Mode (2020-2032)
12.4.8.3. Market Revenue and Forecast, by Applications (2020-2032)
12.4.8.4. Market Revenue and Forecast, by End-User (2020-2032)
12.5. Latin America
12.5.1. Market Revenue and Forecast, by Component (2020-2032)
12.5.2. Market Revenue and Forecast, by Deployment Mode (2020-2032)
12.5.3. Market Revenue and Forecast, by Applications (2020-2032)
12.5.4. Market Revenue and Forecast, by End-User (2020-2032)
12.5.5. Brazil
12.5.5.1. Market Revenue and Forecast, by Component (2020-2032)
12.5.5.2. Market Revenue and Forecast, by Deployment Mode (2020-2032)
12.5.5.3. Market Revenue and Forecast, by Applications (2020-2032)
12.5.5.4. Market Revenue and Forecast, by End-User (2020-2032)
12.5.6. Rest of LATAM
12.5.6.1. Market Revenue and Forecast, by Component (2020-2032)
12.5.6.2. Market Revenue and Forecast, by Deployment Mode (2020-2032)
12.5.6.3. Market Revenue and Forecast, by Applications (2020-2032)
12.5.6.4. Market Revenue and Forecast, by End-User (2020-2032)
Chapter 13. Company Profiles
13.1. Autodesk
13.1.1. Company Overview
13.1.2. Product Offerings
13.1.3. Financial Performance
13.1.4. Recent Initiatives
13.2. OpenAI
13.2.1. Company Overview
13.2.2. Product Offerings
13.2.3. Financial Performance
13.2.4. Recent Initiatives
13.3. Gridics
13.3.1. Company Overview
13.3.2. Product Offerings
13.3.3. Financial Performance
13.3.4. Recent Initiatives
13.4. Cherry
13.4.1. Company Overview
13.4.2. Product Offerings
13.4.3. Financial Performance
13.4.4. Recent Initiatives
13.5. HqO
13.5.1. Company Overview
13.5.2. Product Offerings
13.5.3. Financial Performance
13.5.4. Recent Initiatives
13.6. ai
13.6.1. Company Overview
13.6.2. Product Offerings
13.6.3. Financial Performance
13.6.4. Recent Initiatives
13.7. Io
13.7.1. Company Overview
13.7.2. Product Offerings
13.7.3. Financial Performance
13.7.4. Recent Initiatives
13.8. Matterport
13.8.1. Company Overview
13.8.2. Product Offerings
13.8.3. Financial Performance
13.8.4. Recent Initiatives
13.9. Archistar
13.9.1. Company Overview
13.9.2. Product Offerings
13.9.3. Financial Performance
13.9.4. Recent Initiatives
Chapter 14. Research Methodology
14.1. Primary Research
14.2. Secondary Research
14.3. Assumptions
Chapter 15. Appendix
15.1. About Us
15.2. Glossary of Terms
Thanks for reading you can also get individual chapter-wise sections or region-wise report versions such as North America, Europe, or the Asia Pacific.
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