AI In Weather Prediction Market Size, Share, Opportunities, And Trends By Technology (Machine Learning, Deep Learning, Others) By Services (Weather Forecasting, Climate Modeling, Severe Weather Prediction, Others) By End-User (Aviation, Marine, Agriculture, Energy and Utilities, Transportation and Logistics, Others), And By Geography - Forecasts From 2025 To 2030

AI In Weather Prediction Market Size:

The AI in weather prediction market is set to witness robust growth at a CAGR of 7.92% during the forecast period to be worth US$891.392 million in 2030 from US$608.913 million in 2025.

AI In Weather Prediction Market Trends:

AI weather forecasting technology is in great demand because several business communities need exact weather forecast results. The main industry trends include improving both forecast precision and speed. Computers use satellites, weather stations, and sensor data to detect multiple interlinked patterns that improve future weather estimates. Deep learning algorithms and neural networks improve weather predictions by providing precise results about temperatures, rainfall, and severe weather activities. Through AI technology, predictions updated to individual street and neighborhood areas assist city planning, road management, and farming practices.

AI In Weather Prediction Market Growth Drivers:

• Increasing Frequency of Extreme Weather Events: Weather forecast accuracy becomes more important as extreme weather activities happen globally, such as powerful hurricanes, floods, and droughts. By handling extensive datasets, AI systems help boost prediction quality so emergency services can better plan for disasters. For instance, the European Environment Agency's 2024 data reported that Europe recorded 85,000 to 145,000 human deaths in the past four decades and half a trillion euros in economic damage from certified extreme weather events. In addition, a flood across Central Europe disrupted two million people in September 2024, while heavy rains in Valencia claimed 230 lives and destroyed extensive property in October 2024.
• Enhanced Prediction Accuracy: By processing huge weather data from multiple sources with machine learning tools, AI assists consumers in pinpointing weather patterns better and staying ahead of changing conditions to forecast temperatures, precipitation, and wind outcomes more precisely. The natural adaptability feature of AI assists models processes big data and spotting valuable insights that traditional approaches can't find, leading to growth in demand for this technology in diverse sectors in the years ahead.

AI In Weather Prediction Market Segmentation Analysis by Technology:

• Machine Learning: The utilization of machine learning algorithms is increasing because they handle big atmospheric datasets and make better weather forecasts. These systems recognize historical trends and current signals from datasets, making them important for diverse sectors like agricultural and disaster management operations.
• Deep Learning: Deep learning is witnessing a rise in attention because it finds patterns in extensive datasets that fit specific weather system complexities. These models speed up real-time weather predictions to give accurate updates rapidly during extreme weather events.

AI In Weather Prediction Market Segmentation Analysis by Services:

• Weather Forecasting: The weather forecasting segment is improving through AI because companies need weather information to operate safely. Short-range predictions enable quick decisions that lower damages from weather hazards.
• Climate Modeling: New AI technology controls the way weather simulations help to respond to and prevent climate change impacts. Weather models show improved results and better information about atmospheric airflow patterns through satellite observations and big data methods.

AI In Weather Prediction Market Geographical Outlook:

The AI In Weather Prediction Market report analyzes growth factors across the following five regions:

• North America: North America leads the market due to its advanced technology use, government support, and strong weather data requirements across agriculture and energy businesses. AI helps renewable energy systems work faster and more accurately to generate power better.
• South America: South America is expected to expand its AI weather prediction sector, although it still trails other world regions in development. Improvements in agricultural efficiency through enhanced forecasting present significant market growth opportunities.
• Europe: Markets across the European region will expand notably, with countries such as Germany, the UK, and Italy benefiting from their renewable energy investments. Advancements in weather forecasting technology continue to rise because public safety authorities and economic institutions invest more in advanced systems.
• Middle East and Africa: The Middle East and Africa demonstrate fast growth for AI weather prediction through advanced disaster management system improvements. Governments invest heavily in creating advanced warning systems before dangerous natural disasters, creating major business opportunities.
• Asia-Pacific: The Asia-Pacific region sees fast AI-based forecasting growth because businesses invest more in digital weather forecasting technologies, especially retail stores and the agricultural sector in countries like China and India. In November 2024, the Ministry of Earth Sciences (India) revealed its decision to add AI technology into weather and climate forecasting systems to enhance both accuracy and system performance.

AI In Weather Prediction Market– Competitive Landscape:

• IBM
• Open Climate Fix
• Tomorrow.io
• Climavision

Leading companies in weather prediction technology are working beside new entrants to develop sophisticated solutions and advance AI weather-predicting systems for market success. Climate prediction services will see major changes from technology advancements and market players' collaborations because customers need more exact climate information.

AI In Weather Prediction Market Latest Developments:

• In December 2024, through a partnership with NASA, IBM introduced Prithvi WxC, representing an open-source foundation AI model designed for weather and climate forecast applications. Custom developers program this model to match different purposes, and it runs on standard desktop PCs.
• In October 2024, Atmo collaborated with the Philippines Department of Science and Technology (DOST) 's Advanced Science and Technology Institute (ASTI) and the Philippine Atmospheric Geophysical and Astronomical Services Administration to introduce AI weather forecasting services for DOST.

AI In Weather Prediction Market Scope:

Report Metric	Details
AI In Weather Prediction Market Size in 2025	US$608.913 million
AI In Weather Prediction Market Size in 2030	US$891.392 million
Growth Rate	CAGR of 7.92%
Study Period	2020 to 2030
Historical Data	2020 to 2023
Base Year	2024
Forecast Period	2025 – 2030
Forecast Unit (Value)	USD Million
Segmentation	Technology Services End-User Geography
Geographical Segmentation	North America, South America, Europe, Middle East and Africa, Asia Pacific
List of Major Companies in the AI In Weather Prediction Market	Tomorrow.io (ClimaCell) Google IBM AccuWeather Microsoft
Customization Scope	Free report customization with purchase

 

AI In Weather Prediction Market is analyzed into the following segments:

• By Technology
  • Machine Learning
  • Deep Learning
  • Others
• By Services
  • Weather Forecasting
  • Climate Modeling
  • Severe Weather Prediction
  • Others
• By End-User
  • Aviation
  • Marine
  • Agriculture
  • Energy and Utilities
  • Transportation and Logistics
  • Others
• By Geography
  • North America
    • USA
    • Canada
    • Mexico
  • South America
    • Brazil
    • Argentina
    • Others
  • Europe
    • United Kingdom
    • Germany
    • France
    • Spain
    • Others
  • Middle East and Africa
    • Saudi Arabia
    • UAE
    • Others
  • Asia Pacific
    • China
    • Japan
    • India
    • South Korea
    • Taiwan
    • Others

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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 for the stakeholders

2. RESEARCH METHODOLOGY

2.1. Research Design

2.2. Research Process

3. EXECUTIVE SUMMARY

3.1. Key Findings

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 WEATHER PREDICTION MARKET BY TECHNOLOGY

5.1. Introduction

5.2. Machine Learning

5.3. Deep Learning

5.4. Others

6. AI IN WEATHER PREDICTION MARKET BY SERVICES

6.1. Introduction

6.2. Weather Forecasting

6.3. Climate Modeling

6.4. Severe Weather Prediction

6.5. Others

7. AI IN WEATHER PREDICTION MARKET BY END-USER 

7.1. Introduction

7.2. Aviation

7.3. Marine

7.4. Agriculture

7.5. Energy and Utilities

7.6. Transportation and Logistics

7.7. Other End-Users

8. AI IN WEATHER PREDICTION MARKET BY GEOGRAPHY

8.1. Introduction

8.2. North America

8.2.1. By Technology

8.2.2. By Services

8.2.3. By End User 

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 Technology

8.3.2. By Services

8.3.3. By End User 

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 Technology

8.4.2. By Services

8.4.3. By End User 

8.4.4. By Country

8.4.4.1. United Kingdom

8.4.4.2. Germany

8.4.4.3. France

8.4.4.4. Spain

8.4.4.5. Others

8.5. Middle East and Africa

8.5.1. By Technology

8.5.2. By Services

8.5.3. By End User 

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 Technology

8.6.2. By Services

8.6.3. By End User 

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. Taiwan

8.6.4.6. 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. Tomorrow.io (ClimaCell)

10.2. Google 

10.3. IBM

10.4. AccuWeather

10.5. Microsoft

10.6. Nvidia

10.7. Jupiter Intelligence

10.8. DTN

10.9. Understory

10.10. WeatherFlow

10.11. Open Climate Fix

10.12. Atmo Inc.

10.13.  Climavision

Tomorrow.io (ClimaCell)

Google 

IBM

AccuWeather

Microsoft

Nvidia

Jupiter Intelligence

DTN

Understory

WeatherFlow

Open Climate Fix

Atmo Inc.

 Climavision