Automated Material Handling Equipment Market
Description
Automated Material Handling Equipment Market Summary
The global automated material handling equipment market size was estimated at USD 71.26 billion in 2025 and is projected to reach USD 151.92 Billion by 2033, growing at a CAGR of 10.0% from 2026 to 2033. The market is driven by rapid adoption of automation across warehouses and manufacturing facilities, increasing demand for efficient e-commerce and omnichannel fulfillment operations, rising labor shortages and the need to reduce operational costs, and growing integration of AI, robotics, and smart sensor technologies to enhance throughput and accuracy.
The automated material handling equipment industry is witnessing accelerated growth as organizations prioritize automation to enhance operational efficiency, throughput, and cost competitiveness across warehouses, factories, and distribution centers. Rapid expansion of e-commerce and omnichannel retail is driving sustained investments in high-speed sorting, automated storage and retrieval systems, and intelligent conveyor solutions to manage rising order volumes and shorter delivery timelines. Labor shortages and increasing wage pressures are further strengthening demand for autonomous and semi-autonomous material handling systems that reduce dependency on manual labor while improving workplace safety. Technological advancements, including AI-driven control software, robotics integration, and real-time data analytics, are enabling more flexible, scalable, and predictive material handling operations. Moreover, growing focus on smart factories and Industry 4.0 initiatives is positioning AMH equipment as a strategic enabler for digital transformation and long-term productivity gains.
The rapid growth of e-commerce and omnichannel retail continues to drive large-scale investments in automated material handling equipment. AMH solutions are being deployed to manage high order volumes, faster fulfillment cycles, and increasing SKU complexity. Automated sorting, picking, and storage systems are enabling retailers and logistics providers to meet same-day and next-day delivery expectations. These systems also enhance accuracy and reduce order processing costs, directly supporting margin improvement. As consumer demand for speed and reliability intensifies, AMH adoption is becoming a strategic priority across fulfillment networks.
Labor shortages and rising workforce costs are reinforcing the role of AMH equipment in reducing reliance on manual handling processes. Automated systems improve workplace safety by minimizing human exposure to repetitive, heavy, and hazardous tasks. Meanwhile, manufacturers are developing energy-efficient AMH solutions to align corporate sustainability and carbon reduction goals. Electric-driven systems and optimized energy consumption are helping organizations lower operating expenses while meeting regulatory and ESG requirements. This combined focus on labor optimization, safety, and sustainability is emerging as a key driver of sustained market growth.
Global Automated Material Handling Equipment Market Report Segmentation
This report forecasts revenue growth at global, regional, and country levels and provides an analysis of the latest industry trends in each of the sub-segments from 2021 to 2033. For this study, Grand View Research has segmented the global automated material handling equipment market report based on product, system type, vertical, and region.
The global automated material handling equipment market size was estimated at USD 71.26 billion in 2025 and is projected to reach USD 151.92 Billion by 2033, growing at a CAGR of 10.0% from 2026 to 2033. The market is driven by rapid adoption of automation across warehouses and manufacturing facilities, increasing demand for efficient e-commerce and omnichannel fulfillment operations, rising labor shortages and the need to reduce operational costs, and growing integration of AI, robotics, and smart sensor technologies to enhance throughput and accuracy.
The automated material handling equipment industry is witnessing accelerated growth as organizations prioritize automation to enhance operational efficiency, throughput, and cost competitiveness across warehouses, factories, and distribution centers. Rapid expansion of e-commerce and omnichannel retail is driving sustained investments in high-speed sorting, automated storage and retrieval systems, and intelligent conveyor solutions to manage rising order volumes and shorter delivery timelines. Labor shortages and increasing wage pressures are further strengthening demand for autonomous and semi-autonomous material handling systems that reduce dependency on manual labor while improving workplace safety. Technological advancements, including AI-driven control software, robotics integration, and real-time data analytics, are enabling more flexible, scalable, and predictive material handling operations. Moreover, growing focus on smart factories and Industry 4.0 initiatives is positioning AMH equipment as a strategic enabler for digital transformation and long-term productivity gains.
The rapid growth of e-commerce and omnichannel retail continues to drive large-scale investments in automated material handling equipment. AMH solutions are being deployed to manage high order volumes, faster fulfillment cycles, and increasing SKU complexity. Automated sorting, picking, and storage systems are enabling retailers and logistics providers to meet same-day and next-day delivery expectations. These systems also enhance accuracy and reduce order processing costs, directly supporting margin improvement. As consumer demand for speed and reliability intensifies, AMH adoption is becoming a strategic priority across fulfillment networks.
Labor shortages and rising workforce costs are reinforcing the role of AMH equipment in reducing reliance on manual handling processes. Automated systems improve workplace safety by minimizing human exposure to repetitive, heavy, and hazardous tasks. Meanwhile, manufacturers are developing energy-efficient AMH solutions to align corporate sustainability and carbon reduction goals. Electric-driven systems and optimized energy consumption are helping organizations lower operating expenses while meeting regulatory and ESG requirements. This combined focus on labor optimization, safety, and sustainability is emerging as a key driver of sustained market growth.
Global Automated Material Handling Equipment Market Report Segmentation
This report forecasts revenue growth at global, regional, and country levels and provides an analysis of the latest industry trends in each of the sub-segments from 2021 to 2033. For this study, Grand View Research has segmented the global automated material handling equipment market report based on product, system type, vertical, and region.
- Product Outlook (Volume, Thousand Units, 2021 - 2033)
- Robots
- Automated Storage and Retrieval System (AS/RS)
- Unit Load
- Mid & Mini Load
- Vertical Lift Module (VLM)
- Carousel
- Shuttle
- Conveyors Systems
- Sortation Systems
- Cranes
- Warehouse Management System (WMS)
- Collaborative Robots
- Autonomous Mobile Robots (AMR)
- Goods-to-Person Picking Robots
- Self-driving Forklifts
- Autonomous Inventory Robots
- Unmanned Aerial Vehicles
- Automated Guided Vehicle (AGV)
- Tow Vehicle
- Unit Load Carrier
- Pallet Truck
- Forklift Truck
- Hybrid Vehicles
- Others
- Product Outlook (Revenue, USD Million, 2021 - 2033)
- Robots
- Automated Storage and Retrieval System (AS/RS)
- Unit Load
- Mid & Mini Load
- Vertical Lift Module (VLM)
- Carousel
- Shuttle
- Conveyors Systems
- Sortation Systems
- Cranes
- Warehouse Management System (WMS)
- Collaborative Robots
- Autonomous Mobile Robots (AMR)
- Goods-to-Person Picking Robots
- Self-driving Forklifts
- Autonomous Inventory Robots
- Unmanned Aerial Vehicles
- Automated Guided Vehicle (AGV)
- Tow Vehicle
- Unit Load Carrier
- Pallet Truck
- Forklift Truck
- Hybrid Vehicles
- Others
- System Type Outlook (Revenue, USD Million, 2021 - 2033)
- Unit Load Material Handling
- Bulk Load Material Handling
- Vertical Outlook (Volume, Thousand Units; Revenue, USD Million, 2021 - 2033)
- Automotive
- Semiconductor & Electronics
- E-Commerce
- Healthcare
- Metals & Heavy Machinery
- Food & Beverages
- Chemicals
- 3PL
- Aviation
- Others
- Regional Outlook (Revenue, USD Million, 2021 - 2033)
- North America
- U.S.
- Canada
- Europe
- UK
- Germany
- France
- Asia Pacific
- East Asia
- China
- Japan
- South Korea
- Hong Kong
- Taiwan
- India
- Thailand
- Indonesia
- Vietnam
- Singapore
- Malaysia
- Australia
- Latin America
- Mexico
- Columbia
- Chile
- Argentina
- Caribbean Region
- Middle East and Africa (MEA)
Table of Contents
204 Pages
- Chapter 1. Methodology and Scope
- 1.1. Market Segmentation & Scope
- 1.2. Market Definitions
- 1.2.1. Component Segment
- 1.2.2. Technology Segment
- 1.2.3. Functionality Segment
- 1.2.4. Application Segment
- 1.2.5. End Use
- 1.3. Information analysis
- 1.3.1. Market formulation & data visualization
- 1.4. Data validation & publishing
- 1.5. Information Procurement
- 1.5.1. Primary Research
- 1.6. Information or Data Analysis
- 1.7. Market Formulation & Validation
- 1.8. Market Model
- 1.9. Total Market: CAGR Calculation
- 1.10. Objectives
- 1.10.1. Objective 1
- 1.10.2. Objective 2
- Chapter 2. Executive Summary
- 2.1. Market Outlook
- 2.2. Segment Snapshot
- 2.3. Competitive Insights Landscape
- Chapter 3. AI in Genomics Market Variables, Trends & Scope
- 3.1. Market Lineage Outlook
- 3.1.1. Parent market outlook
- 3.1.2. Related/ancillary market outlook.
- 3.2. Market Dynamics
- 3.2.1. Market driver analysis
- 3.2.2. Market restraint analysis
- 3.2.3. Market opportunity analysis
- 3.2.4. Market challenges analysis
- 3.3. AI in Genomics Market Analysis Tools
- 3.3.1. Industry Analysis - Porter’s
- 3.3.1.1. Supplier power
- 3.3.1.2. Buyer power
- 3.3.1.3. Substitution threat
- 3.3.1.4. Threat of new entrant
- 3.3.1.5. Competitive rivalry
- 3.3.2. PESTEL Analysis
- 3.3.2.1. Political landscape
- 3.3.2.2. Technological landscape
- 3.3.2.3. Economic landscape
- 3.3.2.4. Environmental Landscape
- 3.3.2.5. Legal Landscape
- 3.3.2.6. Social Landscape
- Chapter 4. AI in Genomics Market: Component Estimates & Trend Analysis
- 4.1. Segment Dashboard
- 4.2. Global AI in Genomics Market Component Movement Analysis
- 4.3. Global AI in Genomics Market Size & Trend Analysis, by Component, 2021 to 2033 (USD Million)
- 4.4. Software
- 4.4.1. Market estimates and forecasts, 2021 to 2033 (USD Million)
- 4.5. Hardware
- 4.5.1. Market estimates and forecasts, 2021 to 2033 (USD Million)
- 4.6. Services
- 4.6.1. Market estimates and forecasts, 2021 to 2033 (USD Million)
- Chapter 5. AI in Genomics Market: Technology Estimates & Trend Analysis
- 5.1. Segment Dashboard
- 5.2. Global AI in Genomics Market Technology Movement Analysis
- 5.3. Global AI in Genomics Market Size & Trend Analysis, by Technology, 2021 to 2033 (USD Million)
- 5.4. Machine Learning Algorithms
- 5.4.1. Market estimates and forecasts, 2021 to 2033 (USD Million)
- 5.4.2. Deep learning
- 5.4.2.1. Market estimates and forecasts, 2021 to 2033 (USD Million)
- 5.4.3. Supervised
- 5.4.3.1. Market estimates and forecasts, 2021 to 2033 (USD Million)
- 5.4.4. Unsupervised
- 5.4.4.1. Market estimates and forecasts, 2021 to 2033 (USD Million)
- 5.4.5. Others
- 5.4.5.1. Market estimates and forecasts, 2021 to 2033 (USD Million)
- 5.5. Computer Vision
- 5.5.1. Market estimates and forecasts, 2021 to 2033 (USD Million)
- Chapter 6. AI in Genomics Market: Functionality Estimates & Trend Analysis
- 6.1. Segment Dashboard
- 6.2. Global AI in Genomics Market Functionality Movement Analysis
- 6.3. Global AI in Genomics Market Size & Trend Analysis, by Functionality, 2021 to 2033 (USD Million)
- 6.4. Genome Sequencing
- 6.4.1. Market estimates and forecasts, 2021 to 2033 (USD Million)
- 6.5. Gene Editing
- 6.5.1. Market estimates and forecasts, 2021 to 2033 (USD Million)
- 6.5.2. Others
- 6.5.3. Market estimates and forecasts, 2021 to 2033 (USD Million)
- Chapter 7. AI in Genomics Market: Application Estimates & Trend Analysis
- 7.1. Segment Dashboard
- 7.2. Global AI in Genomics Market Application Movement Analysis
- 7.3. Global AI in Genomics Market Size & Trend Analysis, by Application, 2021 to 2033 (USD Million)
- 7.4. Drug Discovery & Development
- 7.4.1. Market estimates and forecasts, 2021 to 2033 (USD Million)
- 7.5. Precision Medicine
- 7.5.1. Market estimates and forecasts, 2021 to 2033 (USD Million)
- 7.6. Diagnostics
- 7.6.1. Market estimates and forecasts, 2021 to 2033 (USD Million)
- 7.7. Other Applications
- 7.7.1. Market estimates and forecasts, 2021 to 2033 (USD Million)
- Chapter 8. AI in Genomics Market: End Use Estimates & Trend Analysis
- 8.1. Segment Dashboard
- 8.2. Global AI in Genomics Market End Use Movement Analysis
- 8.3. Global AI in Genomics Market Size & Trend Analysis, by End Use, 2021 to 2033 (USD Million)
- 8.4. Pharmaceutical and Biotech Companies
- 8.4.1. Market estimates and forecasts, 2021 to 2033 (USD Million)
- 8.5. Healthcare Providers
- 8.5.1. Market estimates and forecasts, 2021 to 2033 (USD Million)
- 8.6. Research Centers
- 8.6.1. Market estimates and forecasts, 2021 to 2033 (USD Million)
- 8.7. Others
- 8.7.1. Market estimates and forecasts, 2021 to 2033 (USD Million)
- Chapter 9. AI in Genomics Market: Regional Estimates & Trend Analysis
- 9.1. Regional Market Share Analysis, 2025 & 2033
- 9.2. Regional Market Dashboard
- 9.3. Market Size & Forecasts Trend Analysis, 2021 to 2033:
- 9.4. North America
- 9.4.1. U.S.
- 9.4.1.1. Key country dynamics
- 9.4.1.2. Regulatory framework
- 9.4.1.3. Competitive scenario
- 9.4.1.4. U.S. market estimates and forecasts, 2021 to 2033 (USD Million)
- 9.4.2. Canada
- 9.4.2.1. Key country dynamics
- 9.4.2.2. Regulatory framework
- 9.4.2.3. Competitive scenario
- 9.4.2.4. Canada market estimates and forecasts, 2021 to 2033 (USD Million)
- 9.4.3. Mexico
- 9.4.3.1. Key country dynamics
- 9.4.3.2. Regulatory framework
- 9.4.3.3. Competitive scenario
- 9.4.3.4. Mexico market estimates and forecasts, 2021 to 2033 (USD Million)
- 9.5. Europe
- 9.5.1. UK
- 9.5.1.1. Key country dynamics
- 9.5.1.2. Regulatory framework
- 9.5.1.3. Competitive scenario
- 9.5.1.4. UK market estimates and forecasts, 2021 to 2033 (USD Million)
- 9.5.2. Germany
- 9.5.2.1. Key country dynamics
- 9.5.2.2. Regulatory framework
- 9.5.2.3. Competitive scenario
- 9.5.2.4. Germany market estimates and forecasts, 2021 to 2033 (USD Million)
- 9.5.3. France
- 9.5.3.1. Key country dynamics
- 9.5.3.2. Regulatory framework
- 9.5.3.3. Competitive scenario
- 9.5.3.4. France market estimates and forecasts, 2021 to 2033 (USD Million)
- 9.5.4. Italy
- 9.5.4.1. Key country dynamics
- 9.5.4.2. Regulatory framework
- 9.5.4.3. Competitive scenario
- 9.5.4.4. Italy market estimates and forecasts, 2021 to 2033 (USD Million)
- 9.5.5. Spain
- 9.5.5.1. Key country dynamics
- 9.5.5.2. Regulatory framework
- 9.5.5.3. Competitive scenario
- 9.5.5.4. Spain market estimates and forecasts, 2021 to 2033 (USD Million)
- 9.5.6. Norway
- 9.5.6.1. Key country dynamics
- 9.5.6.2. Regulatory framework
- 9.5.6.3. Competitive scenario
- 9.5.6.4. Norway market estimates and forecasts, 2021 to 2033 (USD Million)
- 9.5.7. Sweden
- 9.5.7.1. Key country dynamics
- 9.5.7.2. Regulatory framework
- 9.5.7.3. Competitive scenario
- 9.5.7.4. Sweden market estimates and forecasts, 2021 to 2033 (USD Million)
- 9.5.8. Denmark
- 9.5.8.1. Key country dynamics
- 9.5.8.2. Regulatory framework
- 9.5.8.3. Competitive scenario
- 9.5.8.4. Denmark market estimates and forecasts, 2021 to 2033 (USD Million)
- 9.6. Asia Pacific
- 9.6.1. Japan
- 9.6.1.1. Key country dynamics
- 9.6.1.2. Regulatory framework
- 9.6.1.3. Competitive scenario
- 9.6.1.4. Japan market estimates and forecasts, 2021 to 2033 (USD Million)
- 9.6.2. China
- 9.6.2.1. Key country dynamics
- 9.6.2.2. Regulatory framework
- 9.6.2.3. Competitive scenario
- 9.6.2.4. China market estimates and forecasts, 2021 to 2033 (USD Million)
- 9.6.3. India
- 9.6.3.1. Key country dynamics
- 9.6.3.2. Regulatory framework
- 9.6.3.3. Competitive scenario
- 9.6.3.4. India market estimates and forecasts, 2021 to 2033 (USD Million)
- 9.6.4. Australia
- 9.6.4.1. Key country dynamics
- 9.6.4.2. Regulatory framework
- 9.6.4.3. Competitive scenario
- 9.6.4.4. Australia market estimates and forecasts, 2021 to 2033 (USD Million)
- 9.6.5. South Korea
- 9.6.5.1. Key country dynamics
- 9.6.5.2. Regulatory framework
- 9.6.5.3. Competitive scenario
- 9.6.5.4. South Korea market estimates and forecasts, 2021 to 2033 (USD Million)
- 9.6.6. Thailand
- 9.6.6.1. Key country dynamics
- 9.6.6.2. Regulatory framework
- 9.6.6.3. Competitive scenario
- 9.6.6.4. Thailand market estimates and forecasts, 2021 to 2033 (USD Million)
- 9.7. Latin America
- 9.7.1. Brazil
- 9.7.1.1. Key country dynamics
- 9.7.1.2. Regulatory framework
- 9.7.1.3. Competitive scenario
- 9.7.1.4. Brazil market estimates and forecasts, 2021 to 2033 (USD Million)
- 9.7.2. Argentina
- 9.7.2.1. Key country dynamics
- 9.7.2.2. Regulatory framework
- 9.7.2.3. Competitive scenario
- 9.7.2.4. Argentina market estimates and forecasts, 2021 to 2033 (USD Million)
- 9.8. MEA
- 9.8.1. South Africa
- 9.8.1.1. Key country dynamics
- 9.8.1.2. Regulatory framework
- 9.8.1.3. Competitive scenario
- 9.8.1.4. South Africa market estimates and forecasts, 2021 to 2033 (USD Million)
- 9.8.2. Saudi Arabia
- 9.8.2.1. Key country dynamics
- 9.8.2.2. Regulatory framework
- 9.8.2.3. Competitive scenario
- 9.8.2.4. Saudi Arabia market estimates and forecasts, 2021 to 2033 (USD Million)
- 9.8.3. UAE
- 9.8.3.1. Key country dynamics
- 9.8.3.2. Regulatory framework
- 9.8.3.3. Competitive scenario
- 9.8.3.4. UAE market estimates and forecasts, 2021 to 2033 (USD Million)
- 9.8.4. Kuwait
- 9.8.4.1. Key country dynamics
- 9.8.4.2. Regulatory framework
- 9.8.4.3. Competitive scenario
- 9.8.4.4. Kuwait market estimates and forecasts, 2021 to 2033 (USD Million)
- Chapter 10. Competitive Landscape
- 10.1. Company/Competition Categorization
- 10.2. Strategy Mapping
- 10.3. Company Market Position Analysis, 2025
- 10.4. Company Profiles/Listing
- 10.4.1. Microsoft Corporation
- 10.4.1.1. Company overview
- 10.4.1.2. Financial performance
- 10.4.1.3. Product benchmarking
- 10.4.1.4. Strategic initiatives
- 10.4.2. NVIDIA Corporation
- 10.4.2.1. Company overview
- 10.4.2.2. Financial performance
- 10.4.2.3. Product benchmarking
- 10.4.2.4. Strategic initiatives
- 10.4.3. DEEP GENOMICS
- 10.4.3.1. Company overview
- 10.4.3.2. Financial performance
- 10.4.3.3. Product benchmarking
- 10.4.3.4. Strategic initiatives
- 10.4.4. Data4Cure, Inc.
- 10.4.4.1. Company overview
- 10.4.4.2. Financial performance
- 10.4.4.3. Product benchmarking
- 10.4.4.4. Strategic initiatives
- 10.4.5. Freenome Holdings, Inc.
- 10.4.5.1. Company overview
- 10.4.5.2. Financial performance
- 10.4.5.3. Product benchmarking
- 10.4.5.4. Strategic initiatives
- 10.4.6. Thermo Fisher Scientific
- 10.4.6.1. Company overview
- 10.4.6.2. Financial performance
- 10.4.6.3. Product benchmarking
- 10.4.6.4. Strategic initiatives
- 10.4.7. Illumina, Inc.
- 10.4.7.1. Company overview
- 10.4.7.2. Financial performance
- 10.4.7.3. Product benchmarking
- 10.4.7.4. Strategic initiatives
- 10.4.8. SOPHiA GENETICS
- 10.4.8.1. Company overview
- 10.4.8.2. Financial performance
- 10.4.8.3. Product benchmarking
- 10.4.8.4. Strategic initiatives
- 10.4.9. BenevolentAI
- 10.4.9.1. Company overview
- 10.4.9.2. Financial performance
- 10.4.9.3. Product benchmarking
- 10.4.9.4. Strategic initiatives
- 10.4.10. Fabric Genomics
- 10.4.10.1. Company overview
- 10.4.10.2. Financial performance
- 10.4.10.3. Product benchmarking
- 10.4.10.4. Strategic initiatives
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