Artificial Intelligence In Disaster Response And Emergency Management Market Size, Share, Trends, Opportunity, And Forecast To 2033 | Amazon Inc.; Alphabet Inc.; Microsoft Corporation; Huawei Technologies Co. Ltd.; Deloitte Touche Tohmatsu Limited.

The artificial intelligence in disaster response and emergency management global market report 2024 from The Business Research Company provides comprehensive market statistics, including global market size, regional shares, competitor market share, detailed segments, trends, and opportunities. This report offers an in-depth analysis of current and future industry scenarios, delivering a complete perspective for thriving in the industrial automation software market.

Artificial Intelligence In Disaster Response And Emergency Management Market, 2024 report by The Business Research Company offers comprehensive insights into the current state of the market and highlights future growth opportunities.

Market Size –
The artificial intelligence in disaster response and emergency management market size has grown strongly in recent years. It will grow from $129.31 billion in 2023 to $140.96 billion in 2024 at a compound annual growth rate (CAGR) of 9%. The growth in the historic period can be attributed to increased frequency and severity of disasters, advances in artificial intelligence (AI), cost reduction and efficiency, data availability and integration, public safety and government mandates.

The artificial intelligence in disaster response and emergency management market size is expected to see strong growth in the next few years. It will grow to $201.41 billion in 2028 at a compound annual growth rate (CAGR) of 9.3%. The growth in the forecast period can be attributed to AI-powered robotics and drones, integration with smart cities, climate change impact, AI-driven predictive analytics. Major trends in the forecast period include AI integration with disaster recovery plans, expansion of IoT and sensor networks, rise of AI-powered predictive analytics, adoption of AI-powered robotics and drones, smart cities and ai for disaster management.

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Scope Of Artificial Intelligence In Disaster Response And Emergency Management Market
The Business Research Company’s reports encompass a wide range of information, including:

1. Market Size (Historic and Forecast): Analysis of the market’s historical performance and projections for future growth.

2. Drivers: Examination of the key factors propelling market growth.

3. Trends: Identification of emerging trends and patterns shaping the market landscape.

4. Key Segments: Breakdown of the market into its primary segments and their respective performance.

5. Focus Regions and Geographies: Insight into the most critical regions and geographical areas influencing the market.

6. Macro Economic Factors: Assessment of broader economic elements impacting the market.

Artificial Intelligence In Disaster Response And Emergency Management Market Overview

Market Drivers –
The increasing frequency and severity of disasters are expected to propel the growth of artificial intelligence in the disaster response and emergency management market going forward. Disasters are sudden, catastrophic events that cause significant harm, destruction, and disruption to communities, environments, and economies. A complex interplay of natural phenomena, human activities, and the impacts of climate change drives the frequency and severity of disasters. Artificial intelligence in disaster response and emergency management is used to analyze vast amounts of data from various sources to provide real-time insights, predict disaster impacts, optimize resource allocation, and improve decision-making during crises. For instance, according to the World Disasters Report 2022 by the International Federation of Red Cross and Red Crescent Societies, a France-based non-profit organization, in 2021, the count of disasters was  529, affecting roughly 121.3 million people, with 14,577 documented deaths, surged from a total of 433 disasters in 2020, encompassing both technological incidents and those induced by natural hazards, impacted around 99.0 million individuals and led to 15,396 fatalities. Therefore, the increasing frequency and severity of disasters are driving the growth of artificial intelligence in disaster response and emergency management.

Market Trends –
Major companies operating in artificial intelligence in disaster response and emergency management markets are developing new AI damage recovery solutions such as AI Property, to advance the assessment process. AI Property is an artificial intelligence solution enabling homeowners to swiftly assess and report external damage to buildings caused by natural disasters through a mobile-friendly app, expediting insurance claims and recovery processes. For instance, in January 2022, Tractable, a US-based software company, in collaboration with Verisk, a US-based analytics company, launched AI Property, an innovative tool for fast home damage assessment after natural disasters. This AI-powered solution allows homeowners to use a mobile-friendly app to quickly assess property damage by submitting photos to Tractable’s platform. The AI, trained on a database of claims, provides damage assessments to insurers within a day, a process that used to take months.

The artificial intelligence in disaster response and emergency management market covered in this report is segmented –
1) By Type: Natural Language Processing (NLP), Machine Learning, Computer Vision, Robotics, Speech Recognition
2) By Technology: Remote Sensing, Internet of Things (IOT) Sensors, Geographic Information Systems (GIS), Drones And Unmanned Aerial Vehicles (UAVs), Cloud Computing, Big Data Analytics
3) By Application: Earthquake Prediction And Monitoring, Flood Detection And Management, Wildfire Monitoring And Prediction, Hurricane And Cyclone Tracking, Tsunami Early Warning Systems, Search And Rescue Operations, Damage Assessment And Recovery Planning
4) By End-User: Government Agencies And Authorities, Non-Governmental Organizations (NGOs), Research Institutions And Universities, Disaster Response Teams, Emergency Management Agencies

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Regional Insights –
North America was the largest region in the artificial intelligence in disaster response and emergency management market in 2023. The regions covered in the artificial intelligence in disaster response and emergency management market report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.

Key Companies –
Major companies operating in the artificial intelligence in disaster response and emergency management market report are Amazon Inc.; Alphabet Inc.; Microsoft Corporation; Huawei Technologies Co. Ltd.; Deloitte Touche Tohmatsu Limited; Hitachi Ltd.; Siemens AG; Raytheon Technologies Corporation; Intel Corporation; Accenture PLC; International Business Machines Corporation; Cisco Systems Inc.; General Dynamics Corporation; Northrop Grumman Corporation; Honeywell International Inc.; NVIDIA Corporation; BAE Systems plc; Thales Group; NEC Corporation; Leidos Holdings Inc.; Booz Allen Hamilton Holding Corporation; Motorola Solutions Inc.; Teledyne Technologies Incorporated; Palantir Technologies Inc

Table of Contents
1. Executive Summary
2. Artificial Intelligence In Disaster Response And Emergency Management Market Characteristics
3. Artificial Intelligence In Disaster Response And Emergency Management Market Trends And Strategies
4. Artificial Intelligence In Disaster Response And Emergency Management Market – Macro Economic Scenario
5. Global Artificial Intelligence In Disaster Response And Emergency Management Market Size and Growth

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32. Global Artificial Intelligence In Disaster Response And Emergency Management Market Competitive Benchmarking
33. Global Artificial Intelligence In Disaster Response And Emergency Management Market Competitive Dashboard
34. Key Mergers And Acquisitions In The Artificial Intelligence In Disaster Response And Emergency Management Market
35. Artificial Intelligence In Disaster Response And Emergency Management Market Future Outlook and Potential Analysis
36. Appendix

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