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AI in Environmental Sustainability Market

AI in Environmental Sustainability Market Size, Share & Trends Analysis Report, By Type (Machine Learning, Natural Language Processing (NLP), Computer Vision, Deep Learning, Expert Systems and Robotics and Automation); By Application, By End-User Industry, By Region, Forecasts, 2024-2031

Report ID : 2753 | Published : 2024-09-25 | Pages: 180 | Format: PDF/EXCEL

The AI in Environmental Sustainability Market Size was valued at USD 14.6 Bn in 2023 and is predicted to reach USD 56.9 Bn by 2031 at a 19.1% CAGR during the forecast period for 2024-2031.

ai in environmental sustainability

The field of environmental sustainability is rapidly transforming due to artificial intelligence (AI). This potent technology is used to combat several issues, such as resource conservation and climate change. The incorporation of AI in environmental activities has started to show encouraging effects. Climate modelling and prediction are two main areas where AI has a big impact. Scientists may now create more accurate climate forecasts due to the analysis of enormous datasets by sophisticated AI algorithms. Thus, catastrophic weather occurrences like storms, droughts, and wildfires are better anticipated and governments and groups lessen their consequences. AI is not only improving prediction but also resource management. With AI, for example, optimizing energy use in buildings is becoming more effective.

AI in environmental sustainability is being driven by several factors, including technological advancements, rising investment in AI, growing strategic collaboration among the market players, and many others. However, the market's growth is restricted by variables like a shortage of skilled workforce, data privacy and security concerns, technical limitations, and others. Furthermore, advancements in NLP and consumer demand for green products are major potential opportunities for market growth during the projected period.

Competitive Landscape

Some of the Major Key Players in the AI in Environmental Sustainability Market are

  • Microsoft Corporation
  • IBM Corporation
  • Google LLC
  • Amazon Web Services (AWS)
  • Intel Corporation
  • NVIDIA Corporation
  • Siemens AG
  • General Electric (GE)
  • Schneider Electric SE
  • Accenture plc
  • Oracle Corporation
  • Enablon (Wolters Kluwer)
  • SAP SE
  • C3.ai Inc.
  • SAS Institute Inc.
  • ABB Ltd.
  • Wipro Limited
  • Hitachi, Ltd.
  • Cisco Systems, Inc.
  • Envision Energy
  • CleanCloud Technologies
  • Huawei Technologies Co., Ltd.
  • Ecobot
  • ClimateAI
  • Green Energy Hub
  • Others

Market Segmentation:

The AI in environmental sustainability market is segmented based on type, application and end-use industry. Based on type, the market is segmented as machine learning, natural language processing (NLP), computer vision, deep learning, expert systems and robotics and automation. By application, the market is segmented into climate change mitigation, renewable energy optimization, environmental monitoring and assessment, waste management and recycling, emission reduction and control, conservation and biodiversity, smart agriculture and precision farming, water management and conservation, sustainable urban planning and green building and energy efficiency. Based on end-user industry, the industry is bifurcated into energy and utilities, agriculture, transportation and logistics, manufacturing, healthcare and life sciences, government and public sector, retail and consumer goods, education and research and others.

Based On Type, The Computer Vision Segment Is Accounted As A Major Contributor To The AI In Environmental Sustainability Market

The computer vision category is expected to hold a significant share of the global AI market in environmental sustainability. The industry is expanding due to ongoing advancements in computer vision technology, including stronger machine-learning models, more sophisticated image-processing algorithms, and higher-resolution cameras. These developments improve the precision and effectiveness of environmental monitoring applications. Furthermore, computer vision technologies for environmental sustainability are growing in several industries, including forestry, urban planning, and agriculture. A more comprehensive range of applications leads to an increase in revenue.

The Energy and Utilities Segment Witnessed Growth at a Rapid Rate

The energy and utilities segment is projected to grow rapidly in the global AI in environmental sustainability market. The rising worldwide energy demand fuels the need for more sustainable and effective energy management solutions. AI reduces environmental effects while assisting in meeting this demand. AI applications in the industry are also expanding due to encouraging government regulations and incentives for using renewable energy sources and energy efficiency. Subsidies and regulations promote investment in AI-powered solutions. Additionally, a sizable amount of public, private, and venture capital financing supports the advancement and application of AI technology in the energy and utility sectors. This investment fuels innovation and market growth.

In The Region, North America AI In Environmental Sustainability Market Holds A Significant Revenue Share.

The North American AI in the environmental sustainability market is expected to register the highest market share in revenue in the near future. AI is being heavily funded by corporate funds, government subsidies, and venture capital for environmental sustainability. The industry is developing and innovating thanks to this financial backing. Additionally, several initiatives and regulations at the federal and state levels encourage the creation and application of AI technology for environmental sustainability. Proposals such as Canada's Climate Plan and the United States' Green New Deal promote the application of cutting-edge technologies to environmental problems. Additionally, top research centres and colleges in North America are advancing the area by conducting state-of-the-art studies on AI applications for environmental sustainability. In addition, Asia Pacific is projected to grow rapidly in the global AI in environmental sustainability market due to rising investment by the market players.

Recent Developments:

  • In July 2024, Product Footprinting, a new AI-powered technology designed to help businesses calculate carbon emissions for products and lessen environmental effects, was introduced by the sustainability platform CO2 AI. Leveraging artificial intelligence, Paris-based CO2 AI offers solutions designed to assist large and complex companies in measuring impact and identifying levers to decrease impact at scale. The company cites a study by CO2 AI and BCG that shows only 38% of businesses obtain sufficient product-level data from suppliers, and claims that the new solution addresses the requirement for more precise and quick product carbon foot printing.

AI in Environmental Sustainability Market Report Scope

Report Attribute

Specifications

Market Size Value In 2023

USD 14.6 Bn

Revenue Forecast In 2031

USD 56.9 Bn

Growth Rate CAGR

CAGR of 19.1% from 2024 to 2031

Quantitative Units

Representation of revenue in US$ Bn and CAGR from 2024 to 2031

Historic Year

2019 to 2023

Forecast Year

2024-2031

Report Coverage

The forecast of revenue, the position of the company, the competitive market structure, growth prospects, and trends

Segments Covered

By Type, By Application, By End-Use Industry and By Region

Regional Scope

North America; Europe; Asia Pacific; Latin America; Middle East & Africa

Country Scope

U.S.; Canada; U.K.; Germany; China; India; Japan; Brazil; Mexico; France; Italy; Spain; South East Asia; South Korea

Competitive Landscape

Microsoft Corporation, IBM Corporation, Google LLC, Amazon Web Services (AWS), Intel Corporation, NVIDIA Corporation, Siemens AG, General Electric (GE), Schneider Electric SE, Accenture plc, Oracle Corporation, Enablon (Wolters Kluwer), SAP SE, C3.ai Inc., SAS Institute Inc., ABB Ltd., Wipro Limited, Hitachi, Ltd., Cisco Systems, Inc., Envision Energy, CleanCloud Technologies, Huawei Technologies Co., Ltd., Ecobot, ClimateAI, Green Energy Hub, and Others.

Customization Scope

Free customization report with the procurement of the report and modifications to the regional and segment scope. Particular Geographic competitive landscape.

Pricing And Available Payment Methods

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Chapter 1. Methodology and Scope
1.1. Research Methodology
1.2. Research Scope & Assumptions

Chapter 2. Executive Summary

Chapter 3. Global AI in Environmental Sustainability Market Snapshot

Chapter 4. Global AI in Environmental Sustainability Market Variables, Trends & Scope
4.1. Market Segmentation & Scope
4.2. Drivers
4.3. Challenges
4.4. Trends
4.5. Investment and Funding Analysis
4.6. Industry Analysis – Porter’s Five Forces Analysis
4.7. Competitive Landscape & Market Share Analysis
4.8. Impact of Covid-19 Analysis

Chapter 5. Market Segmentation 1: by Type Estimates & Trend Analysis
5.1. by Type & Market Share, 2019 & 2031
5.2. Market Size (Value (US$ Mn)) & Forecasts and Trend Analyses, 2019 to 2031 for the following by Type:

5.2.1. Learning
5.2.2. Natural Language Processing (NLP)
5.2.3. Computer Vision
5.2.4. Deep Learning
5.2.5. Expert Systems
5.2.6. Robotics and Automation

Chapter 6. Market Segmentation 2: by End-User Industry Estimates & Trend Analysis
6.1. by End-User Industry & Market Share, 2019 & 2031
6.2. Market Size (Value (US$ Mn)) & Forecasts and Trend Analyses, 2019 to 2031 for the following by End-User Industry:

6.2.1. Energy and Utilities
6.2.2. Agriculture
6.2.3. Transportation and Logistics
6.2.4. Manufacturing
6.2.5. Healthcare and Life Sciences
6.2.6. Government and Public Sector
6.2.7. Retail and Consumer Goods
6.2.8. Education and Research
6.2.9. Others

Chapter 7. Market Segmentation 3: by Application Estimates & Trend Analysis
7.1. by Application & Market Share, 2019 & 2031
7.2. Market Size (Value (US$ Mn)) & Forecasts and Trend Analyses, 2019 to 2031 for the following by Application:

7.2.1. Climate Change Mitigation
7.2.2. Renewable Energy Optimization
7.2.3. Environmental Monitoring and Assessment
7.2.4. Waste Management and Recycling
7.2.5. Emission Reduction and Control
7.2.6. Conservation and Biodiversity
7.2.7. Smart Agriculture and Precision Farming
7.2.8. Water Management and Conservation
7.2.9. Sustainable Urban Planning
7.2.10. Green Building and Energy Efficiency

Chapter 8. AI in Environmental Sustainability Market Segmentation 4: Regional Estimates & Trend Analysis

8.1. North America
8.1.1. North America AI in Environmental Sustainability Market Revenue (US$ Million) Estimates and Forecasts by Type, 2024-2031
8.1.2. North America AI in Environmental Sustainability Market Revenue (US$ Million) Estimates and Forecasts by End-User Industry, 2024-2031
8.1.3. North America AI in Environmental Sustainability Market Revenue (US$ Million) Estimates and Forecasts by Application, 2024-2031
8.1.4. North America AI in Environmental Sustainability Market Revenue (US$ Million) Estimates and Forecasts by country, 2024-2031

8.2. Europe
8.2.1. Europe AI in Environmental Sustainability Market Revenue (US$ Million) Estimates and Forecasts by Type, 2024-2031
8.2.2. Europe AI in Environmental Sustainability Market Revenue (US$ Million) Estimates and Forecasts by End-User Industry, 2024-2031
8.2.3. Europe AI in Environmental Sustainability Market Revenue (US$ Million) Estimates and Forecasts by Application, 2024-2031
8.2.4. Europe AI in Environmental Sustainability Market Revenue (US$ Million) Estimates and Forecasts by country, 2024-2031

8.3. Asia Pacific
8.3.1. Asia Pacific AI in Environmental Sustainability Market Revenue (US$ Million) Estimates and Forecasts by Type, 2024-2031
8.3.2. Asia Pacific AI in Environmental Sustainability Market Revenue (US$ Million) Estimates and Forecasts by End-User Industry, 2024-2031
8.3.3. Asia-Pacific AI in Environmental Sustainability Market Revenue (US$ Million) Estimates and Forecasts by Application, 2024-2031
8.3.4. Asia Pacific AI in Environmental Sustainability Market Revenue (US$ Million) Estimates and Forecasts by country, 2024-2031

8.4. Latin America
8.4.1. Latin America AI in Environmental Sustainability Market Revenue (US$ Million) Estimates and Forecasts by Type, 2024-2031
8.4.2. Latin America AI in Environmental Sustainability Market Revenue (US$ Million) Estimates and Forecasts by End-User Industry, 2024-2031
8.4.3. Latin America AI in Environmental Sustainability Market Revenue (US$ Million) Estimates and Forecasts by Application, 2024-2031
8.4.4. Latin America AI in Environmental Sustainability Market Revenue (US$ Million) Estimates and Forecasts by country, 2024-2031

8.5. Middle East & Africa
8.5.1. Middle East & Africa AI in Environmental Sustainability Market Revenue (US$ Million) Estimates and Forecasts by Type, 2024-2031
8.5.2. Middle East & Africa AI in Environmental Sustainability Market Revenue (US$ Million) Estimates and Forecasts by End-User Industry, 2024-2031
8.5.3. Middle East & Africa AI in Environmental Sustainability Market Revenue (US$ Million) Estimates and Forecasts by Application, 2024-2031
8.5.4. Middle East & Africa AI in Environmental Sustainability Market Revenue (US$ Million) Estimates and Forecasts by country, 2024-2031

Chapter 9. Competitive Landscape
9.1. Major Mergers and Acquisitions/Strategic Alliances
9.2. Company Profiles

9.2.1. Microsoft Corporation
9.2.2. IBM Corporation
9.2.3. Google LLC
9.2.4. Amazon Web Services (AWS)
9.2.5. Intel Corporation
9.2.6. NVIDIA Corporation
9.2.7. Siemens AG
9.2.8. General Electric (GE)
9.2.9. Schneider Electric SE
9.2.10. Accenture plc
9.2.11. Oracle Corporation
9.2.12. Enablon (Wolters Kluwer)
9.2.13. SAP SE
9.2.14. C3.ai Inc.
9.2.15. SAS Institute Inc.
9.2.16. ABB Ltd.
9.2.17. Wipro Limited
9.2.18. Hitachi, Ltd.
9.2.19. Cisco Systems, Inc.
9.2.20. Envision Energy
9.2.21. CleanCloud Technologies
9.2.22. Huawei Technologies Co., Ltd.
9.2.23. Ecobot
9.2.24. ClimateAI
9.2.25. Green Energy Hub
9.2.26. Other Market Players

 

Segmentation of AI in Environmental Sustainability Market

AI in Environmental Sustainability Market- By Type

  • Machine Learning
  • Natural Language Processing (NLP)
  • Computer Vision
  • Deep Learning,
  • Expert Systems
  • Robotics and Automation

ai in environmental sustainability

AI in Environmental Sustainability Market- By Application

  • Climate Change Mitigation
  • Renewable Energy Optimization
  • Environmental Monitoring and Assessment
  • Waste Management and Recycling
  • Emission Reduction and Control
  • Conservation and Biodiversity
  • Smart Agriculture and Precision Farming
  • Water Management and Conservation
  • Sustainable Urban Planning
  • Green Building and Energy Efficiency

AI in Environmental Sustainability Market- By End-Use Industry

  • Energy and Utilities
  • Agriculture
  • Transportation and Logistics
  • Manufacturing
  • Healthcare and Lifesciences
  • Government and Public Sector
  • Retail and Consumer Goods
  • Education and Research
  • Others

AI in Environmental Sustainability Market- By Region

North America-

  • The US
  • Canada
  • Mexico

Europe-

  • Germany
  • The UK
  • France
  • Italy
  • Spain
  • Rest of Europe

Asia-Pacific-

  • China
  • Japan
  • India
  • South Korea
  • South East Asia
  • Rest of Asia Pacific

Latin America-

  • Brazil
  • Argentina
  • Rest of Latin America

 Middle East & Africa-

  • GCC Countries
  • South Africa
  • Rest of Middle East and Africa

 

InsightAce Analytic follows a standard and comprehensive market research methodology focused on offering the most accurate and precise market insights. The methods followed for all our market research studies include three significant steps – primary research, secondary research, and data modeling and analysis - to derive the current market size and forecast it over the forecast period. In this study, these three steps were used iteratively to generate valid data points (minimum deviation), which were cross-validated through multiple approaches mentioned below in the data modeling section.

Through secondary research methods, information on the market under study, its peer, and the parent market was collected. This information was then entered into data models. The resulted data points and insights were then validated by primary participants.

Based on additional insights from these primary participants, more directional efforts were put into doing secondary research and optimize data models. This process was repeated till all data models used in the study produced similar results (with minimum deviation). This way, this iterative process was able to generate the most accurate market numbers and qualitative insights.

Secondary research

The secondary research sources that are typically mentioned to include, but are not limited to:

  • Company websites, financial reports, annual reports, investor presentations, broker reports, and SEC filings.
  • External and internal proprietary databases, regulatory databases, and relevant patent analysis
  • Statistical databases, National government documents, and market reports
  • Press releases, news articles, and webcasts specific to the companies operating in the market

The paid sources for secondary research like Factiva, OneSource, Hoovers, and Statista

Primary Research:

Primary research involves telephonic interviews, e-mail interactions, as well as face-to-face interviews for each market, category, segment, and subsegment across geographies

The contributors who typically take part in such a course include, but are not limited to: 

  • Industry participants: CEOs, CBO, CMO, VPs, marketing/ type managers, corporate strategy managers, and national sales managers, technical personnel, purchasing managers, resellers, and distributors.
  • Outside experts: Valuation experts, Investment bankers, research analysts specializing in specific markets
  • Key opinion leaders (KOLs) specializing in unique areas corresponding to various industry verticals
  • End-users: Vary mainly depending upon the market

Data Modeling and Analysis:

In the iterative process (mentioned above), data models received inputs from primary as well as secondary sources. But analysts working on these models were the key. They used their extensive knowledge and experience about industry and topic to make changes and fine-tuning these models as per the product/service under study.

The standard data models used while studying this market were the top-down and bottom-up approaches and the company shares analysis model. However, other methods were also used along with these – which were specific to the industry and product/service under study.

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Frequently Asked Questions

How big is the AI in Environmental Sustainability Market Size?

The AI in Environmental Sustainability Market is expected to grow at a 19.1% CAGR during the forecast period for 2024-2031.

Microsoft Corporation, IBM Corporation, Google LLC, Amazon Web Services (AWS), Intel Corporation, NVIDIA Corporation, Siemens AG, General Electric (GE

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