Selected research
Market Outlook & Growth Opportunities
Global AI in Disaster Prediction Market Outlook and Growth Opportunities 2026
Market perspective
The global AI in Disaster Prediction market was valued at US$ million in 2026 and is projected to reach US$ million by 2032, implying a compound annual growth rate (CAGR) of % over 2026-2032.
The North America market for AI in Disaster Prediction is projected to increase from US$ million in 2026 to US$ million by 2032, at a CAGR of % over 2026-2032.
The Europe market for AI in Disaster Prediction is projected to increase from US$ million in 2026 to US$ million by 2032, at a CAGR of % over 2026-2032.
Read the full market overview
The Asia Pacific market for AI in Disaster Prediction is projected to increase from US$ million in 2026 to US$ million by 2032, at a CAGR of % over 2026-2032.
In China, the AI in Disaster Prediction market is projected to increase from US$ million in 2026 to US$ million by 2032, at a CAGR of % over 2026-2032.
Major global companies in the AI in Disaster Prediction market include OroraTech, Spectee, NTT Corporation, LiXia, AI Property, One Concern, Zindi, Appier and Fujitsu, among others. In 2025, the top three vendors together accounted for approximately % of global market revenue.
This report provides an overview of the global AI in Disaster Prediction market in terms of revenue and gross margin, analyzing global market trends using historical revenue data for 2021-2025, estimates for 2026, and projected CAGRs through 2032.
The study covers key producers of AI in Disaster Prediction and market revenue by major regions and countries, assesses future market potential, and highlights priority regions and countries for segmenting the market into sub-sectors, with country-specific market value data for the U.S., Canada, Mexico, Brazil, China, Japan, South Korea, Southeast Asia, India, Germany, the U.K., Italy, the Middle East, Africa, and other countries.
The report also presents AI in Disaster Prediction revenue, market share, and industry ranking for the main companies for 2021-2026, identifies the major stakeholders in the global market, and analyzes their competitive landscape and market positioning based on recent developments and segmental revenues.
Across the 2021-2026 period, the analysis compares revenue growth and profitability profiles by company, distinguishing participants with sustained expansion from those with more cyclical performance, and relates these patterns to differences in regional exposure, product portfolios, and application focus in the global AI in Disaster Prediction market.
AI in Disaster Prediction Segment by Company
OroraTech
Spectee
NTT Corporation
LiXia
AI Property
One Concern
Zindi
Appier
Fujitsu
Sipremo
AI in Disaster Prediction Segment by Type
Machine Learning
Natural Language Processing
Computer Vision
Others
AI in Disaster Prediction Segment by Application
Wildfire Detection
Flood Forecasting
Earthquake Response
Others
AI in Disaster Prediction Segment by Region
North America
United States
Canada
Mexico
Europe
Germany
France
U.K.
Italy
Russia
Spain
Netherlands
Switzerland
Sweden
Poland
Asia-Pacific
China
Japan
South Korea
India
Australia
Taiwan
Southeast Asia
South America
Brazil
Argentina
Chile
Colombia
Middle East & Africa
Egypt
South Africa
Israel
Türkiye
GCC Countries
Study Objectives
1. To analyze and research the global AI in Disaster Prediction status and future forecast, involving, revenue, growth rate (CAGR), market share, historical and forecast.
2. To present the AI in Disaster Prediction key companies, revenue, market share, and recent developments.
3. To split the AI in Disaster Prediction breakdown data by regions, type, companies, and application.
4. To analyze the global and key regions AI in Disaster Prediction market potential and advantage, opportunity and challenge, restraints, and risks.
5. To identify AI in Disaster Prediction significant trends, drivers, influence factors in global and regions.
6. To analyze AI in Disaster Prediction competitive developments such as expansions, agreements, new product launches, and acquisitions in the market.
Reasons to Buy This Report
1. This report will help the readers to understand the competition within the industries and strategies for the competitive environment to enhance the potential profit. The report also focuses on the competitive landscape of the global AI in Disaster Prediction market, and introduces in detail the market share, industry ranking, competitor ecosystem, market performance, new product development, operation situation, expansion, and acquisition. etc. of the main players, which helps the readers to identify the main competitors and deeply understand the competition pattern of the market.
2. This report will help stakeholders to understand the global industry status and trends of AI in Disaster Prediction and provides them with information on key market drivers, restraints, challenges, and opportunities.
3. This report will help stakeholders to understand competitors better and gain more insights to strengthen their position in their businesses. The competitive landscape section includes the market share and rank (in sales and value), competitor ecosystem, new product development, expansion, and acquisition.
4. This report stays updated with novel technology integration, features, and the latest developments in the market.
5. This report helps stakeholders to gain insights into which regions to target globally.
6. This report helps stakeholders to gain insights into the end-user perception concerning the adoption of AI in Disaster Prediction.
7. This report helps stakeholders to identify some of the key players in the market and understand their valuable contribution.
Chapter Outline
Chapter 1: Introduces the report scope of the report, global total market size.
Chapter 2: Analysis key trends, drivers, challenges, and opportunities within the global AI in Disaster Prediction industry.
Chapter 3: Detailed analysis of AI in Disaster Prediction company competitive landscape, revenue market share, latest development plan, merger, and acquisition information, etc.
Chapter 4: Provides the analysis of various market segments by type, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different market segments.
Chapter 5: Provides the analysis of various market segments by application, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different downstream markets.
Chapter 6: Sales value of AI in Disaster Prediction in regional level. It provides a quantitative analysis of the market size and development potential of each region and introduces the market development, future development prospects, market space, and market size of key country in the world.
Chapter 7: Sales value of AI in Disaster Prediction in country level. It provides sigmate data by type, and by application for each country/region.
Chapter 8: Provides profiles of key players, introducing the basic situation of the main companies in the market in detail, including revenue, gross margin, product introduction, recent development, etc.
Chapter 9: Concluding Insights.
More report detail
Tables and figures
Scope & coverage.
Types
- Machine Learning
- Natural Language Processing
- Computer Vision
- Others
Applications
- Wildfire Detection
- Flood Forecasting
- Earthquake Response
- Others
Companies covered
- OroraTech
- Spectee
- NTT Corporation
- LiXia
- AI Property
- One Concern
- Zindi
- Appier
- Fujitsu
- Sipremo
Inside the report.
1 Market Overview
- 1.1 Product Definition
- 1.2 Global AI in Disaster Prediction Market Size, 2021 VS 2025 VS 2032
- 1.3 Global AI in Disaster Prediction Market Size (2021-2032)
- 1.4 Assumptions and Limitations
- 1.5 Study Goals and Objectives
2 AI in Disaster Prediction Market Dynamics
- 2.1 AI in Disaster Prediction Industry Trends
- 2.2 AI in Disaster Prediction Industry Drivers
- 2.3 AI in Disaster Prediction Industry Opportunities and Challenges
- 2.4 AI in Disaster Prediction Industry Restraints
3 AI in Disaster Prediction Market by Company
- 3.1 Global AI in Disaster Prediction Company Revenue Ranking in 2025
- 3.2 Global AI in Disaster Prediction Revenue by Company (2021-2026)
- 3.3 Global AI in Disaster Prediction Company Ranking (2024-2026)
- 3.4 Global AI in Disaster Prediction Company Manufacturing Base and Headquarters
- 3.5 Global AI in Disaster Prediction Company Product Type and Application
- 3.6 Global AI in Disaster Prediction Company Establishment Date
- 3.7 Market Competitive Analysis
- 3.7.1 Global AI in Disaster Prediction Market Concentration Ratio (CR5 and HHI)
- 3.7.2 Global Top 5 and 10 Company Market Share by Revenue in 2025
- 3.7.3 2025 AI in Disaster Prediction Tier 1, Tier 2, and Tier 3 Companies
- 3.8 Mergers and Acquisitions Expansion
4 AI in Disaster Prediction Market by Type
- 4.1 AI in Disaster Prediction Type Introduction
- 4.1.1 Machine Learning
- 4.1.2 Natural Language Processing
- 4.1.3 Computer Vision
- 4.1.4 Others
- 4.2 Global AI in Disaster Prediction Sales Value by Type
- 4.2.1 Global AI in Disaster Prediction Sales Value by Type (2021 VS 2025 VS 2032)
- 4.2.2 Global AI in Disaster Prediction Sales Value by Type (2021-2032)
- 4.2.3 Global AI in Disaster Prediction Sales Value Share by Type (2021-2032)
5 AI in Disaster Prediction Market by Application
- 5.1 AI in Disaster Prediction Application Introduction
- 5.1.1 Wildfire Detection
- 5.1.2 Flood Forecasting
- 5.1.3 Earthquake Response
- 5.1.4 Others
- 5.2 Global AI in Disaster Prediction Sales Value by Application
- 5.2.1 Global AI in Disaster Prediction Sales Value by Application (2021 VS 2025 VS 2032)
- 5.2.2 Global AI in Disaster Prediction Sales Value by Application (2021-2032)
- 5.2.3 Global AI in Disaster Prediction Sales Value Share by Application (2021-2032)
6 AI in Disaster Prediction Regional Value Analysis
- 6.1 Global AI in Disaster Prediction Sales Value by Region: 2021 VS 2025 VS 2032
- 6.2 Global AI in Disaster Prediction Sales Value by Region (2021-2032)
- 6.2.1 Global AI in Disaster Prediction Sales Value by Region: 2021-2026
- 6.2.2 Global AI in Disaster Prediction Sales Value by Region (2027-2032)
- 6.3 North America
- 6.3.1 North America AI in Disaster Prediction Sales Value (2021-2032)
- 6.3.2 North America AI in Disaster Prediction Sales Value Share by Country, 2025 VS 2032
- 6.4 Europe
- 6.4.1 Europe AI in Disaster Prediction Sales Value (2021-2032)
- 6.4.2 Europe AI in Disaster Prediction Sales Value Share by Country, 2025 VS 2032
- 6.5 Asia-Pacific
- 6.5.1 Asia-Pacific AI in Disaster Prediction Sales Value (2021-2032)
- 6.5.2 Asia-Pacific AI in Disaster Prediction Sales Value Share by Country, 2025 VS 2032
- 6.6 South America
- 6.6.1 South America AI in Disaster Prediction Sales Value (2021-2032)
- 6.6.2 South America AI in Disaster Prediction Sales Value Share by Country, 2025 VS 2032
- 6.7 Middle East & Africa
- 6.7.1 Middle East & Africa AI in Disaster Prediction Sales Value (2021-2032)
- 6.7.2 Middle East & Africa AI in Disaster Prediction Sales Value Share by Country, 2025 VS 2032
7 AI in Disaster Prediction Country-level Value Analysis
- 7.1 Global AI in Disaster Prediction Sales Value by Country: 2021 VS 2025 VS 2032
- 7.2 Global AI in Disaster Prediction Sales Value by Country (2021-2032)
- 7.2.1 Global AI in Disaster Prediction Sales Value by Country (2021-2026)
- 7.2.2 Global AI in Disaster Prediction Sales Value by Country (2027-2032)
- 7.3 USA
- 7.3.1 USA AI in Disaster Prediction Sales Value Growth Rate (2021-2032)
- 7.3.2 USA AI in Disaster Prediction Sales Value Share by Type, 2025 VS 2032
- 7.3.3 USA AI in Disaster Prediction Sales Value Share by Application, 2025 VS 2032
- 7.4 Canada
- 7.4.1 Canada AI in Disaster Prediction Sales Value Growth Rate (2021-2032)
- 7.4.2 Canada AI in Disaster Prediction Sales Value Share by Type, 2025 VS 2032
- 7.4.3 Canada AI in Disaster Prediction Sales Value Share by Application, 2025 VS 2032
- 7.5 Mexico
- 7.5.1 Mexico AI in Disaster Prediction Sales Value Growth Rate (2021-2032)
- 7.5.2 Mexico AI in Disaster Prediction Sales Value Share by Type, 2025 VS 2032
- 7.5.3 Mexico AI in Disaster Prediction Sales Value Share by Application, 2025 VS 2032
- 7.6 Germany
- 7.6.1 Germany AI in Disaster Prediction Sales Value Growth Rate (2021-2032)
- 7.6.2 Germany AI in Disaster Prediction Sales Value Share by Type, 2025 VS 2032
- 7.6.3 Germany AI in Disaster Prediction Sales Value Share by Application, 2025 VS 2032
- 7.7 France
- 7.7.1 France AI in Disaster Prediction Sales Value Growth Rate (2021-2032)
- 7.7.2 France AI in Disaster Prediction Sales Value Share by Type, 2025 VS 2032
- 7.7.3 France AI in Disaster Prediction Sales Value Share by Application, 2025 VS 2032
- 7.8 U.K.
- 7.8.1 U.K. AI in Disaster Prediction Sales Value Growth Rate (2021-2032)
- 7.8.2 U.K. AI in Disaster Prediction Sales Value Share by Type, 2025 VS 2032
- 7.8.3 U.K. AI in Disaster Prediction Sales Value Share by Application, 2025 VS 2032
- 7.9 Italy
- 7.9.1 Italy AI in Disaster Prediction Sales Value Growth Rate (2021-2032)
- 7.9.2 Italy AI in Disaster Prediction Sales Value Share by Type, 2025 VS 2032
- 7.9.3 Italy AI in Disaster Prediction Sales Value Share by Application, 2025 VS 2032
- 7.10 Spain
- 7.10.1 Spain AI in Disaster Prediction Sales Value Growth Rate (2021-2032)
- 7.10.2 Spain AI in Disaster Prediction Sales Value Share by Type, 2025 VS 2032
- 7.10.3 Spain AI in Disaster Prediction Sales Value Share by Application, 2025 VS 2032
- 7.11 Russia
- 7.11.1 Russia AI in Disaster Prediction Sales Value Growth Rate (2021-2032)
- 7.11.2 Russia AI in Disaster Prediction Sales Value Share by Type, 2025 VS 2032
- 7.11.3 Russia AI in Disaster Prediction Sales Value Share by Application, 2025 VS 2032
- 7.12 Netherlands
- 7.12.1 Netherlands AI in Disaster Prediction Sales Value Growth Rate (2021-2032)
- 7.12.2 Netherlands AI in Disaster Prediction Sales Value Share by Type, 2025 VS 2032
- 7.12.3 Netherlands AI in Disaster Prediction Sales Value Share by Application, 2025 VS 2032
- 7.13 Nordic Countries
- 7.13.1 Nordic Countries AI in Disaster Prediction Sales Value Growth Rate (2021-2032)
- 7.13.2 Nordic Countries AI in Disaster Prediction Sales Value Share by Type, 2025 VS 2032
- 7.13.3 Nordic Countries AI in Disaster Prediction Sales Value Share by Application, 2025 VS 2032
- 7.14 China
- 7.14.1 China AI in Disaster Prediction Sales Value Growth Rate (2021-2032)
- 7.14.2 China AI in Disaster Prediction Sales Value Share by Type, 2025 VS 2032
- 7.14.3 China AI in Disaster Prediction Sales Value Share by Application, 2025 VS 2032
- 7.15 Japan
- 7.15.1 Japan AI in Disaster Prediction Sales Value Growth Rate (2021-2032)
- 7.15.2 Japan AI in Disaster Prediction Sales Value Share by Type, 2025 VS 2032
- 7.15.3 Japan AI in Disaster Prediction Sales Value Share by Application, 2025 VS 2032
- 7.16 South Korea
- 7.16.1 South Korea AI in Disaster Prediction Sales Value Growth Rate (2021-2032)
- 7.16.2 South Korea AI in Disaster Prediction Sales Value Share by Type, 2025 VS 2032
- 7.16.3 South Korea AI in Disaster Prediction Sales Value Share by Application, 2025 VS 2032
- 7.17 India
- 7.17.1 India AI in Disaster Prediction Sales Value Growth Rate (2021-2032)
- 7.17.2 India AI in Disaster Prediction Sales Value Share by Type, 2025 VS 2032
- 7.17.3 India AI in Disaster Prediction Sales Value Share by Application, 2025 VS 2032
- 7.18 Australia
- 7.18.1 Australia AI in Disaster Prediction Sales Value Growth Rate (2021-2032)
- 7.18.2 Australia AI in Disaster Prediction Sales Value Share by Type, 2025 VS 2032
- 7.18.3 Australia AI in Disaster Prediction Sales Value Share by Application, 2025 VS 2032
- 7.19 Southeast Asia
- 7.19.1 Southeast Asia AI in Disaster Prediction Sales Value Growth Rate (2021-2032)
- 7.19.2 Southeast Asia AI in Disaster Prediction Sales Value Share by Type, 2025 VS 2032
- 7.19.3 Southeast Asia AI in Disaster Prediction Sales Value Share by Application, 2025 VS 2032
- 7.20 Brazil
- 7.20.1 Brazil AI in Disaster Prediction Sales Value Growth Rate (2021-2032)
- 7.20.2 Brazil AI in Disaster Prediction Sales Value Share by Type, 2025 VS 2032
- 7.20.3 Brazil AI in Disaster Prediction Sales Value Share by Application, 2025 VS 2032
- 7.21 Argentina
- 7.21.1 Argentina AI in Disaster Prediction Sales Value Growth Rate (2021-2032)
- 7.21.2 Argentina AI in Disaster Prediction Sales Value Share by Type, 2025 VS 2032
- 7.21.3 Argentina AI in Disaster Prediction Sales Value Share by Application, 2025 VS 2032
- 7.22 Chile
- 7.22.1 Chile AI in Disaster Prediction Sales Value Growth Rate (2021-2032)
- 7.22.2 Chile AI in Disaster Prediction Sales Value Share by Type, 2025 VS 2032
- 7.22.3 Chile AI in Disaster Prediction Sales Value Share by Application, 2025 VS 2032
- 7.23 Colombia
- 7.23.1 Colombia AI in Disaster Prediction Sales Value Growth Rate (2021-2032)
- 7.23.2 Colombia AI in Disaster Prediction Sales Value Share by Type, 2025 VS 2032
- 7.23.3 Colombia AI in Disaster Prediction Sales Value Share by Application, 2025 VS 2032
- 7.24 Peru
- 7.24.1 Peru AI in Disaster Prediction Sales Value Growth Rate (2021-2032)
- 7.24.2 Peru AI in Disaster Prediction Sales Value Share by Type, 2025 VS 2032
- 7.24.3 Peru AI in Disaster Prediction Sales Value Share by Application, 2025 VS 2032
- 7.25 Saudi Arabia
- 7.25.1 Saudi Arabia AI in Disaster Prediction Sales Value Growth Rate (2021-2032)
- 7.25.2 Saudi Arabia AI in Disaster Prediction Sales Value Share by Type, 2025 VS 2032
- 7.25.3 Saudi Arabia AI in Disaster Prediction Sales Value Share by Application, 2025 VS 2032
- 7.26 Israel
- 7.26.1 Israel AI in Disaster Prediction Sales Value Growth Rate (2021-2032)
- 7.26.2 Israel AI in Disaster Prediction Sales Value Share by Type, 2025 VS 2032
- 7.26.3 Israel AI in Disaster Prediction Sales Value Share by Application, 2025 VS 2032
- 7.27 UAE
- 7.27.1 UAE AI in Disaster Prediction Sales Value Growth Rate (2021-2032)
- 7.27.2 UAE AI in Disaster Prediction Sales Value Share by Type, 2025 VS 2032
- 7.27.3 UAE AI in Disaster Prediction Sales Value Share by Application, 2025 VS 2032
- 7.28 Turkey
- 7.28.1 Turkey AI in Disaster Prediction Sales Value Growth Rate (2021-2032)
- 7.28.2 Turkey AI in Disaster Prediction Sales Value Share by Type, 2025 VS 2032
- 7.28.3 Turkey AI in Disaster Prediction Sales Value Share by Application, 2025 VS 2032
- 7.29 Iran
- 7.29.1 Iran AI in Disaster Prediction Sales Value Growth Rate (2021-2032)
- 7.29.2 Iran AI in Disaster Prediction Sales Value Share by Type, 2025 VS 2032
- 7.29.3 Iran AI in Disaster Prediction Sales Value Share by Application, 2025 VS 2032
- 7.30 Egypt
- 7.30.1 Egypt AI in Disaster Prediction Sales Value Growth Rate (2021-2032)
- 7.30.2 Egypt AI in Disaster Prediction Sales Value Share by Type, 2025 VS 2032
- 7.30.3 Egypt AI in Disaster Prediction Sales Value Share by Application, 2025 VS 2032
8 Company Profiles
- 8.1 OroraTech
- 8.1.1 OroraTech Company Information
- 8.1.2 OroraTech Business Overview
- 8.1.3 OroraTech AI in Disaster Prediction Revenue and Gross Margin (2021-2026)
- 8.1.4 OroraTech AI in Disaster Prediction Product Portfolio
- 8.1.5 OroraTech Recent Developments
- 8.2 Spectee
- 8.2.1 Spectee Company Information
- 8.2.2 Spectee Business Overview
- 8.2.3 Spectee AI in Disaster Prediction Revenue and Gross Margin (2021-2026)
- 8.2.4 Spectee AI in Disaster Prediction Product Portfolio
- 8.2.5 Spectee Recent Developments
- 8.3 NTT Corporation
- 8.3.1 NTT Corporation Company Information
- 8.3.2 NTT Corporation Business Overview
- 8.3.3 NTT Corporation AI in Disaster Prediction Revenue and Gross Margin (2021-2026)
- 8.3.4 NTT Corporation AI in Disaster Prediction Product Portfolio
- 8.3.5 NTT Corporation Recent Developments
- 8.4 LiXia
- 8.4.1 LiXia Company Information
- 8.4.2 LiXia Business Overview
- 8.4.3 LiXia AI in Disaster Prediction Revenue and Gross Margin (2021-2026)
- 8.4.4 LiXia AI in Disaster Prediction Product Portfolio
- 8.4.5 LiXia Recent Developments
- 8.5 AI Property
- 8.5.1 AI Property Company Information
- 8.5.2 AI Property Business Overview
- 8.5.3 AI Property AI in Disaster Prediction Revenue and Gross Margin (2021-2026)
- 8.5.4 AI Property AI in Disaster Prediction Product Portfolio
- 8.5.5 AI Property Recent Developments
- 8.6 One Concern
- 8.6.1 One Concern Company Information
- 8.6.2 One Concern Business Overview
- 8.6.3 One Concern AI in Disaster Prediction Revenue and Gross Margin (2021-2026)
- 8.6.4 One Concern AI in Disaster Prediction Product Portfolio
- 8.6.5 One Concern Recent Developments
- 8.7 Zindi
- 8.7.1 Zindi Company Information
- 8.7.2 Zindi Business Overview
- 8.7.3 Zindi AI in Disaster Prediction Revenue and Gross Margin (2021-2026)
- 8.7.4 Zindi AI in Disaster Prediction Product Portfolio
- 8.7.5 Zindi Recent Developments
- 8.8 Appier
- 8.8.1 Appier Company Information
- 8.8.2 Appier Business Overview
- 8.8.3 Appier AI in Disaster Prediction Revenue and Gross Margin (2021-2026)
- 8.8.4 Appier AI in Disaster Prediction Product Portfolio
- 8.8.5 Appier Recent Developments
- 8.9 Fujitsu
- 8.9.1 Fujitsu Company Information
- 8.9.2 Fujitsu Business Overview
- 8.9.3 Fujitsu AI in Disaster Prediction Revenue and Gross Margin (2021-2026)
- 8.9.4 Fujitsu AI in Disaster Prediction Product Portfolio
- 8.9.5 Fujitsu Recent Developments
- 8.10 Sipremo
- 8.10.1 Sipremo Company Information
- 8.10.2 Sipremo Business Overview
- 8.10.3 Sipremo AI in Disaster Prediction Revenue and Gross Margin (2021-2026)
- 8.10.4 Sipremo AI in Disaster Prediction Product Portfolio
- 8.10.5 Sipremo Recent Developments
9 Concluding Insights
10 Appendix
- 10.1 Reasons for Doing This Study
- 10.2 Research Methodology
- 10.3 Research Process
- 10.4 Authors List of This Report
- 10.5 Data Source
- 10.5.1 Secondary Sources
- 10.5.2 Primary Sources
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