Artificial Intelligence (AI) In Weather Prediction Market - Strategic Insights and Forecasts (2025-2030)

Description

AI in Weather Prediction Market Size:

The Artificial Intelligence (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.

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This technology delivers hyper-local forecasts, enabling precise predictions for temperature, rainfall, and severe weather events at the street or neighbourhood level. These advancements enable real-time forecasting, supporting city planning, road management, and precision agriculture. For instance, AI-driven forecasts help farmers optimize irrigation and crop planning, while urban planners use them for infrastructure resilience and disaster preparedness. The aviation and logistics sectors also benefit, relying on AI weather predictions for safer and more efficient operations.

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Thus, increasing extreme weather events are driving demand for AI-powered weather forecasting solutions, and growing AI technology adoption is enhancing prediction accuracy across multiple industries. Moreover, advancing machine learning algorithms are improving real-time weather pattern recognition, while rising agricultural needs are boosting AI use for precise crop and irrigation planning.

Key players working in the market include Tomorrow.io (ClimaCell), Google (Alphabet Inc.), IBM, AccuWeather Inc., Microsoft Corporation, NVIDIA Corporation, Jupiter Intelligence Inc., DTN LLC, Understory Inc., WeatherFlow Inc., Open Climate Fix, Atmo Inc., and Climavision Inc.

AI in Weather Prediction Market Trends

• High Demand from Transport and Logistics

There is a growing market for AI weather prediction services in transport and logistics. The market is driven by the advantages offered by weather forecasting services that help in automating the route planning, fuel efficiency, and risk mitigation as weather disrupts schedules, damages infrastructure, and endangers personnel and cargo. ClimaVision offers Horizon AI weather forecasting product suite encompassing Horizon AI Global, HIRES, Point and Subseasonal to Seasonal models offering high-resolution short-term forecasts and probabilistic long-term outlooks.

AI in Weather Prediction Market Dynamics

Market Drivers

• Increasing Frequency of Extreme Weather Events
  Weather forecast accuracy becomes more important as extreme weather events 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 Accuracy Offered by AI-Integrated Weather Prediction Models
  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 in processing 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.

Market Restraints

• High Data Dependency and Quality Issues with High Infrastructure and Implementation Costs
  One of the major challenges faced by the market is the high infrastructure and implementation cost. As the development and deployment of AI-based weather prediction systems require advanced computational infrastructure, satellite data integration, and cloud computing resources, their cost goes higher, making their adoption challenging. Besides, AI weather prediction requires a massive amount of historical and real-time weather data. At the same time, it offers many times inconsistent and low-quality data whose reliability is reduced. Both these factors combine to restrict the adoption of AI in weather prediction, posing key challenges in market growth.

Market Opportunities

• Media Sector Emerging as a Key End-User Opportunity
  Weather forecasts are a cornerstone of local news, attracting millions of daily viewers who rely on them for essential information. This consistent viewership makes the weathercast a lucrative sponsorship opportunity for local stations. The media uses weather forecasts to deliver timely, accurate information to the public, influencing daily decisions and safety measures.

AI-enhanced forecasting, particularly in nowcasting, short-range, and medium-range predictions, enables media outlets to deliver real-time, hyper-local, and highly accurate updates that improve public safety and trust. As per the Pew Research Center, seventy percent of US adults say the weather is the most important news topic to them. AI adoption allows broadcasters to respond to heightened demand during extreme weather events, when viewership surges dramatically.

AI in Weather Prediction Market Segmentation Analysis

By Technology

Based on technology, the market is segmented into machine learning, deep learning, and others. Others include various other technologies used, such as Natural Language Processing, computer vision, or hybrid tools.

Machine Learning will be the key segment

Machine learning holds the dominant share. The segment is growing 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 is Growing

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.

By Components

Services is a high-growth Segment

Services include consulting, implementation, data integration, and managed services. It forms a smaller share than hardware and software; however, it is a high-growth market, driven by the need for skilled deployment, as many users, such as government agencies, insurers, logistics providers, and energy firms, lack in-house AI expertise. For example, companies offer AI-powered consulting and managed services that help organizations integrate short-range prediction tools into operations, while specialized service providers support governments, research institutes, and enterprises in applying AI-driven climate simulations.

AI in Weather Prediction Market Regional Analysis

By region, the market is segmented into North America, South America, the Middle East and Africa, and Asia-Pacific.

• North America
  North America leads the market due to its advanced technology adoption, government support, and strong demand for weather data in the agriculture and energy sectors. AI enhances renewable energy systems, enabling faster and more accurate power generation by optimizing operations based on precise weather forecasts. Despite challenges like high computational costs, cloud computing and AI innovations drive accessibility. The AI weather prediction market is set to expand, fueled by industry applications, climate resilience, and technological advancements.
• 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.
• The 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 in 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. Countries like Indonesia are growing in the AI for weather prediction due to the geographic necessity of being in the tropical region, the most vulnerable region affected by climate change, and is more prone to disasters in the country. Geographical complexity is driving the demand for AI forecasting services to protect lives, infrastructure, and economic activity. Similarly, Thailand’s geography, with its northern mountains, central plains prone to flooding, and southern coastal regions along the Andaman Sea and Gulf of Thailand, creates diverse weather patterns that drive demand for AI weather forecasting for various reasons like agriculture, disaster preparedness, and others.

AI in Weather Prediction Market Competitive Landscape

Key Industry Players

The market is emerging and going through a transformative phase. The market is gaining traction through government funding, climate adaptation needs, and growing tech adoption. It is primarily a fragmented market currently, featuring a mix of big tech giants that offer foundation models, such as Google, Microsoft, and NVIDIA, while companies like IBM and AccuWeather integrate AI into their established platforms. The market also has metrological companies that are integrating AI into their offerings, while it also includes new niche, innovative startups. The market is driven by innovation, leading to high competition in offering key innovative products. Players are increasingly collaborating with governments or NGOs, and are investing in R&D and cloud scalability. Besides, some leading companies in weather prediction technology are working alongside 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.

List of Key Company Profiled

• Google (Alphabet Inc.)
• Microsoft Inc.
• NVIDIA Corporation
• IBM
• AccuWeather
• Atmo Inc.
• Climavision

AI in Weather Prediction Market Key Developments

• Initiative: In February 2025, WMO sponsored the AI Weather Quest. It is a WIPPS Pilot Project by INFCOM, which aimed to innovate and collaborate in numerical weather prediction for the benefit of National Meteorological and Hydrological Services (NMHSs) and end-users worldwide.
• Government-Use Case: In March 2025, the Ministry of Earth Sciences, India, has integrated AI technologies into weather forecasting. It is aimed to enhance the accuracy and efficiency of meteorological predictions, which are crucial for various sectors, including agriculture, disaster management, and urban planning.
• Product Launch: In September 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.
• Collaboration: 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.

Artificial Intelligence (AI) in Weather Prediction Market Scope:

Artificial Intelligence (AI) in Weather Prediction Market Segmentation:

• 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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Table Of Contents

1. EXECUTIVE SUMMARY

2. MARKET SNAPSHOT

2.1. Market Overview

2.2. Market Definition

2.3. Scope of the Study

2.4. Market Segmentation

3. BUSINESS LANDSCAPE

3.1. Market Drivers

3.2. Market Restraints

3.3. Market Opportunities

3.4. Porter’s Five Forces Analysis

3.5. Industry Value Chain Analysis

3.6. Policies and Regulations

3.7. Strategic Recommendations

4. TECHNOLOGICAL OUTLOOK

5. AI IN WEATHER PREDICTION MARKET BY COMPONENT

5.1. Introduction

5.2. Software/Platforms

5.3. Hardware

5.4. Services

6. AI IN WEATHER PREDICTION MARKET BY TECHNOLOGY TYPE

6.1. Introduction

6.2. Machine Learning

6.3. Deep Learning

6.4. Others

7. AI IN WEATHER PREDICTION MARKET BY END-USER

7.1. Introduction

7.2. Aviation

7.3. Marine & Shipping

7.4. Agriculture & Forestry

7.5. Energy and Utilities

7.6. Disaster Management

7.7. Transportation and Logistics

7.8. Media and Consumer Services

7.9. Others

8. AI IN WEATHER PREDICTION MARKET BY GEOGRAPHY

8.1. Introduction

8.2. North America

8.2.1. By Component

8.2.2. By Technology Type

8.2.3. By End-User

8.2.4. By Country

8.2.4.1. United States

8.2.4.2. Canada

8.2.4.3. Mexico

8.3. South America

8.3.1. By Component

8.3.2. By Technology Type

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 Component

8.4.2. By Technology Type

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. Italy

8.4.4.5. Others

8.5. Middle East & Africa

8.5.1. By Component

8.5.2. By Technology Type

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 Component

8.6.2. By Technology Type

8.6.3. By End-User

8.6.4. By Country

8.6.4.1. Japan

8.6.4.2. China

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 (Alphabet Inc.)

10.3. IBM

10.4. AccuWeather, Inc.

10.5. Microsoft Corporation

10.6. NVIDIA Corporation

10.7. Jupiter Intelligence, Inc.

10.8. DTN, LLC

10.9. Understory, Inc.

10.10. WeatherFlow, Inc.

10.11. Open Climate Fix

10.12. Atmo Inc.

10.13. Climavision, Inc.

11. RESEARCH METHODOLOGY

Companies Profiled

Tomorrow.io (ClimaCell)

Google (Alphabet Inc.)

IBM

AccuWeather, Inc.

Microsoft Corporation

NVIDIA Corporation

Jupiter Intelligence, Inc.

DTN, LLC

Understory, Inc.

WeatherFlow, Inc.

Open Climate Fix

Atmo Inc.

Climavision, Inc.

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