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AI in Waste Management Market

AI in Waste Management Market Size, Share & Trends Analysis Report By Waste Type (Industrial Waste, Electronic Waste, Hazardous and Chemical Waste, Plastic and Plastic Product Waste, Biological Waste, and Others), By Technology Type (Predictive Models, Classification Robots, Smart Garbage Bins, and Others), By End User (Industrial, Residential, and Commercial), By Region, And By Segment Forecasts, 2024-2031

Report ID : 2354 | Published : 2024-09-25 | Pages: 180 | Format: PDF/EXCEL

AI in Waste Management Market Size is predicted to show a 35.2% CAGR during the forecast period for 2024-2031.

AI in Waste Management Market info

AI in waste management allows for more precise rate forecasting by analyzing environmental parameters and past data. With this helpful information, waste management businesses can plan the most efficient garbage pick-up routes, guaranteeing punctual service while reducing fuel usage and carbon dioxide emissions. Improved garbage sorting and recycling operations are within reach with the help of AI technology. Plastics, metals, paper, and other types of garbage can be more accurately and efficiently recycled using artificial intelligence algorithms. An efficient waste management system will make good use of its resources, including garbage trucks. This system uses AI to help determine the most efficient garbage collection route, saving time and making better use of available resources.

The technology optimizes the truck's route for better waste management system performance by leveraging real-time updates from smart trash collectors. Furthermore, waste reduction attempts rely heavily on artificial intelligence predictive skills. Businesses can improve their production and inventory management planning using AI-driven predictive analytics, improving demand forecasts' accuracy.

However, the market growth is hampered by the lack of awareness criteria for the safety and health of low code technology in the insurance market and the product's inability to prevent fog in environments with dramatic temperature fluctuations or high AI in waste management. At the same time, if a corporation or municipality installs a smart waste management system, locals may have trouble understanding the technology. As a result of the increasing diversity of trash, it is challenging for AI developers to develop a one-size-fits-all approach to trash management. It is challenging for AI to provide reliable estimates of trash production, recycling, and disposal volumes, particularly in densely populated areas.

The spread of the COVID-19 virus has triggered widespread market volatility and deep economic recession. Artificial intelligence saw a significant slump in the waste management industry due to the strict lockdown established throughout big economies. It is believed that the usage of artificial intelligence in waste management will be hindered by the market's reduced cash liquidity and building and real estate development activities. Significantly reducing demand for residential and commercial buildings and a corresponding decline in existing activity further hindered market expansion.

Competitive Landscape

Some Major Key Players In The AI in Waste Management Market:

  • WM Intellectual Property Holdings LLC,
  • Waste Connections
  • Suez Group
  • Veolia
  • Stericycle, Inc.
  • Republic Services, Inc.
  • Meridiam
  • Hitachi Zosen Corporation
  • Daiseki Co. Ltd.
  • Clean Harbors, Inc
  • BioMedical Waste Solutions, LLC.
  • Biffa
  • Other Prominent Players

Market Segmentation:

The AI in waste management market is segmented based on waste type, technology type, and end user. The waste type segment comprises industrial waste, electronic waste, hazardous and chemical waste, plastic and plastic product waste, biological waste, and others. By technology type, the market is segmented into predictive models, classification robots, smart garbage bins, and others. By end user, the market is segmented into industrial, residential, and commercial.

Based On The Waste Type, The Plastic And Plastic Product Waste Segment Is Accounted As A Major Contributor To The AI In Waste Management Market. 

The plastic and plastic product waste AI in the waste management market is expected to hold a major global market share in 2022. Plastic waste on a global scale is the overuse of plastic and plastic products in many different industries, including manufacturing, consumer goods, and electronics. Many commonly recyclable plastic items, such as bottles, boxes, and cans, end up in landfills. This causes the category to dominate the global market for artificial intelligence in waste management.

Classification Robots Segment To Witness Growth At A Rapid Rate.

The classification robots make up the bulk of acrylic acid ester usage because the robots equipped with AI models can classify garbage according to different types. As these aids businesses in cutting down on operating costs associated with human labour, artificial intelligence becomes more appealing in the waste management industry.

In The Region, The North American AI In Waste Management Market Holds A Significant Revenue Share.

The North American AI in the waste management market is expected to record a large market revenue share in the near future. It can be attributed to because of the government's friendly programs that promote the use of AI in several sectors. In addition, Asia Pacific is estimated to grow rapidly in the global AI waste management market due to the increased necessity for housing and the federal government's heavy focus on infrastructural development. In addition, environmental authorities' rules encouraging eco-friendly housing and tight limitations on landfill operations are anticipated to stimulate area growth.

Recent Developments:

  • In October 2023, Clean Harbors released its sustainability supplement to go along with its latest sustainability report. Additionally, the supplement highlights the positive effects of Clean Harbors' sustainability initiatives on the environment, its customers, and the communities it serves.
  • In September 2023, SUEZ declared the execution of two substantial contracts in the water and waste sectors, which will aid in the realization of China's 2060 goal of carbon neutrality. SUEZ and its historical collaborator in Chongqing worked together to strengthen the water supply system's resilience by constructing a new water treatment facility. The Group initiated its inaugural plastics recovery initiative in China in Shanghai.

AI in Waste Management Market Report Scope

Report Attribute

Specifications

Growth Rate CAGR

CAGR of 35.2 % 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 Waste Type, Technology Type, And End User.

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; Southeast Asia; South Korea

Competitive Landscape

WM Intellectual Property Holdings, LLC, Waste Connections, Suez Group, Veolia, Stericycle, Inc., Republic Services, Inc., Meridiam, Hitachi Zosen Corporation, Daiseki Co. Ltd., and Clean Harbors, Inc.

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

Explore pricing alternatives that are customized to your particular study requirements.

Chapter 1. Methodology and Scope

1.1. Research Methodology

1.2. Research Scope & Assumptions

Chapter 2. Executive Summary

Chapter 3. Global AI in Waste Management Market Snapshot

Chapter 4. Global AI in Waste Management 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 Waste Type Estimates & Trend Analysis

5.1. by Waste Type & Market Share, 2019 & 2031

5.2. Market Size (Value (US$ Mn)) & Forecasts and Trend Analyses, 2019 to 2031 for the following by Waste Type;

5.2.1. Industrial Waste

5.2.2. Electronic Waste

5.2.3. Hazardous and Chemical Waste

5.2.4. Plastic and Plastic Product Waste

5.2.5. Biological Waste

5.2.6. Others

Chapter 6. Market Segmentation 2: by Technology Type Estimates & Trend Analysis

6.1. by Technology Type & Market Share, 2019 & 2031

6.2. Market Size (Value (US$ Mn)) & Forecasts and Trend Analyses, 2019 to 2031 for the following by Technology Type:

6.2.1. Predictive Models

6.2.2. Classification Robots

6.2.3. Smart Garbage Bins

6.2.4. Others

Chapter 7. Market Segmentation 3: by End-user Estimates & Trend Analysis

7.1. by End-user & Market Share, 2019 & 2031

7.2. Market Size (Value (US$ Mn)) & Forecasts and Trend Analyses, 2019 to 2031 for the following by End-user;

7.2.1. Industrial

7.2.2. Residential

7.2.3. Commercial

Chapter 8. AI in Waste Management Market Segmentation 4: Regional Estimates & Trend Analysis

8.1. North America

8.1.1. North America AI in Waste Management Market Revenue (US$ Million) Estimates and Forecasts by Waste Type, 2019-2031

8.1.2. North America AI in Waste Management Market Revenue (US$ Million) Estimates and Forecasts by Technology Type, 2019-2031

8.1.3. North America AI in Waste Management Market Revenue (US$ Million) Estimates and Forecasts by End-user, 2019-2031

8.1.4. North America AI in Waste Management Market Revenue (US$ Million) Estimates and Forecasts by country, 2019-2031

8.2. Europe

8.2.1. Europe AI in Waste Management Market Revenue (US$ Million) Estimates and Forecasts by Waste Type, 2019-2031

8.2.2. Europe AI in Waste Management Market Revenue (US$ Million) Estimates and Forecasts by Technology Type, 2019-2031

8.2.3. Europe AI in Waste Management Market Revenue (US$ Million) Estimates and Forecasts by End-user, 2019-2031

8.2.4. Europe AI in Waste Management Market Revenue (US$ Million) Estimates and Forecasts by country, 2019-2031

8.3. Asia Pacific

8.3.1. Asia Pacific AI in Waste Management Market Revenue (US$ Million) Estimates and Forecasts by Waste Type, 2019-2031

8.3.2. Asia Pacific AI in Waste Management Market Revenue (US$ Million) Estimates and Forecasts by Technology Type, 2019-2031

8.3.3. Asia-Pacific AI in Waste Management Market Revenue (US$ Million) Estimates and Forecasts by End-user ,2019-2031

8.3.4. Asia Pacific AI in Waste Management Market Revenue (US$ Million) Estimates and Forecasts by country, 2019-2031

8.4. Latin America

8.4.1. Latin America AI in Waste Management Market Revenue (US$ Million) Estimates and Forecasts by Waste Type 2019-2031

8.4.2. Latin America AI in Waste Management Market Revenue (US$ Million) Estimates and Forecasts by Technology Type, 2019-2031

8.4.3. Latin America AI in Waste Management Market Revenue (US$ Million) Estimates and Forecasts by End-user, 2019-2031

8.4.4. Latin America AI in Waste Management Market Revenue (US$ Million) Estimates and Forecasts by country, 2019-2031

8.5. Middle East & Africa

8.5.1. Middle East & Africa AI in Waste Management Market Revenue (US$ Million) Estimates and Forecasts by Waste Type, 2019-2031

8.5.2. Middle East & Africa AI in Waste Management Market Revenue (US$ Million) Estimates and Forecasts by Technology Type, 2019-2031

8.5.3. Middle East & Africa AI in Waste Management Market Revenue (US$ Million) Estimates and Forecasts by End-user, 2019-2031

8.5.4. Middle East & Africa AI in Waste Management Market Revenue (US$ Million) Estimates and Forecasts by country, 2019-2031

Chapter 9. Competitive Landscape

9.1. Major Mergers and Acquisitions/Strategic Alliances

9.2. Company Profiles

9.2.1. WM Intellectual Property Holdings LLC,

9.2.2. Waste Connections

9.2.3. Suez Group

9.2.4. Veolia

9.2.5. Stericycle, Inc.

9.2.6. Republic Services, Inc.

9.2.7. Meridiam

9.2.8. Hitachi Zosen Corporation

9.2.9. Daiseki Co. Ltd.

9.2.10. Clean Harbors, Inc

9.2.11. BioMedical Waste Solutions, LLC.

9.2.12. Biffa

9.2.13. Other Prominent Players

Segmentation of AI in Waste Management Market-

AI in Waste Management Market By Waste Type-

  • Industrial Waste
  • Electronic Waste
  • Hazardous and Chemical Waste
  • Plastic and Plastic Product Waste
  • Biological Waste
  • Others

AI in Waste Management Market seg

AI in Waste Management Market By Technology Type-

  • Predictive Models
  • Classification Robots
  • Smart Garbage Bins
  • Others

AI in Waste Management Market By End User-

  • Industrial
  • Residential
  • Commercial

AI in Waste Management 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 the 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.

To know more about the research methodology used for this study, kindly contact us/click here.

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Frequently Asked Questions

What is the AI in Waste Management Market Growth?

Veolia, Stericycle, Inc., Republic Services, Inc., Meridiam, Hitachi Zosen Corporation, Daiseki Co. Ltd., and Clean Harbors, Inc.

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