창고용 AI 로보틱스 시장 : 기능/용도, 로봇 유형, AI 기능, 전개 형태, 최종사용자/업계, 자율 레벨, 지역별 - 시장 규모, 업계 역학, 기회 분석, 예측(2026-2035년)

The global AI robotics in warehousing market is undergoing rapid and transformative expansion, reflecting the growing importance of automation in modern supply chains. In 2025, the market was valued at USD 12.57 billion, and it is projected to reach an impressive USD 102.67 billion by 2035. This remarkable growth corresponds to a compound annual growth rate (CAGR) of 23.37% during the forecast period from 2026 to 2035. Such a steep rise highlights the accelerating adoption of AI-driven robotics as warehouses worldwide strive to meet the increasing demands of efficiency, speed, and accuracy.

Several key factors are driving this market surge. The expansion of e-commerce is a primary catalyst, as online retail continues to reshape consumer behavior by emphasizing fast delivery and vast product assortments. To keep pace with these expectations, warehouses must operate at higher speeds and with greater precision, necessitating advanced robotic systems that can automate complex tasks such as picking, packing, sorting, and inventory management. Additionally, widespread labor shortages in the warehousing sector are intensifying the push towards automation.

Noteworthy Market Developments

As of early 2026, the vendor landscape in the AI robotics in warehousing market has undergone a dramatic transformation, evolving from a fragmented startup ecosystem into a fiercely competitive arena dominated by both consolidated industry giants and hyper-specialized AI disruptors. This shift reflects the maturation of the market, where scale, technological sophistication, and strategic partnerships now define success. Among the leaders, Geek+ stands out as the global volume champion in Autonomous Mobile Robot (AMR) deployment, commanding nearly 50% of the global market share in goods-to-person (G2P) solutions.

In the realm of high-density cubic storage and grocery automation, AutoStore and Symbotic have established themselves as the key players. AutoStore's modular and space-efficient storage system has revolutionized warehouse design, allowing companies to maximize storage capacity in limited spaces. Symbotic, meanwhile, has carved out a leadership position through its deep integration with major U.S. retailers, setting the industry standard for comprehensive end-to-end automation solutions.

Locus Robotics has emerged as the undeniable leader in collaborative AMRs, commonly known as cobots, designed specifically for fulfillment operations. Celebrated for its highly effective Robotics-as-a-Service (RaaS) model and intuitive multi-robot orchestration software, Locus offers a solution that is both scalable and user-friendly. Their cobots work alongside human operators, enhancing productivity without requiring extensive infrastructure changes.

Core Growth Drivers

Increasing warehouse labor costs, coupled with a scarcity of skilled workers, are major factors accelerating the shift toward robotic solutions and driving market growth in the warehousing sector. As labor expenses continue to rise, fueled by wage inflation and heightened competition for qualified personnel, companies face mounting pressure to control operational costs while maintaining high levels of productivity. This financial strain compels warehouse operators to explore automation technologies that can deliver consistent performance without the challenges associated with human labor, such as turnover, training needs, and absenteeism.

Emerging Opportunity Trends

High investment from global retail and logistics companies is expected to create favorable opportunities for the robotics warehousing market, driving rapid expansion and innovation. As these industries face increasing pressure to enhance efficiency, reduce labor costs, and meet growing consumer demand for faster delivery times, they are turning to robotics as a critical solution. The influx of capital from major players worldwide is fueling research, development, and deployment of advanced robotic systems, enabling warehouses to automate more complex tasks and scale operations more effectively.

Barriers to Optimization

Battery degradation and charging bottlenecks present significant challenges that could hamper growth in the AI robotics market, particularly in warehouse environments relying heavily on Autonomous Mobile Robots (AMRs). As fleets expand, the strain on charging infrastructure becomes increasingly apparent. For example, managing a fleet of 200 AMRs requires a well-designed and extensive charging setup capable of supporting continuous operations. Without adequate infrastructure and intelligent management, charging can quickly become a major operational bottleneck.

Detailed Market Segmentation

By robot type, the Automated Guided Vehicles (AGVs) segment commanded a substantial 41% market share in 2024, highlighting their pivotal role in industrial automation and logistics. AGVs have earned a reputation as one of the most dependable and mature robotic technologies available, making them a preferred choice for companies seeking to modernize their operations while minimizing risks. Their proven track record in heavy industry and legacy logistics environments underscores their reliability and effectiveness in handling repetitive material transport tasks in complex and often harsh conditions.

By function and application, the picking and packing segment emerged as the leader in the AI robotics in warehousing market, holding an estimated 39% market share in 2025. This dominance highlights the critical importance of these processes within warehouse operations, where efficiency and accuracy directly impact overall productivity and customer satisfaction. Order picking, in particular, has long been recognized as one of the most labor-intensive and costly activities in traditional logistics, historically accounting for 50% to 55% of total warehouse operating expenses. This significant cost burden has driven companies to seek automation solutions that can streamline picking and packing tasks, reduce errors, and lower labor costs.

By AI capability, the machine learning (ML) and predictive analytics segment established its dominance over the market in 2024, capturing a commanding 42.22% share. This strong foothold underscores the critical role that ML and predictive analytics play in elevating robotic systems from basic automated devices to intelligent, adaptive machines capable of complex decision-making. Without these AI capabilities, a robot's functionality is severely limited, akin to an expensive remote-controlled car that can only follow pre-programmed commands without learning or adapting to its environment.

By end users, the e-commerce and omni-channel retail sector dominates the market with a commanding 44% share, reflecting its critical role in shaping logistics and fulfillment strategies. This prominence is largely driven by the increasing demand for micro-fulfillment centers and the pressure to meet stringent same-day delivery service level agreements (SLAs). As consumer expectations for rapid and reliable delivery continue to rise, retailers are compelled to adopt advanced automation solutions that can handle the complexity and scale of modern order fulfillment.

Segment Breakdown

By AI Capability

• Machine Learning & Predictive Analytics
• Computer Vision & Imaging
• Sensor Fusion & IoT Integration
• Natural Language Processing (NLP)
• Autonomous Navigation & Path Planning
• Others

By Robot Type

• Automated Guided Vehicles (AGVs)
• Towing AGVs
• Unit Load AGVs
• Autonomous Mobile Robots (AMRs)
• Picking AMRs
• Pallet Handling AMRs
• Robotic Arms & Pick-and-Place Robots
• Collaborative Robots (Cobots)
• Sorting & Packaging Robots
• Others

By Function / Application

• Picking & Packing
• Sorting & Distribution
• Inventory Management & Tracking
• Material Transport & Handling
• Loading & Unloading
• Quality Inspection
• Others

By End User / Industry

• E-Commerce & Retail
• Third-Party Logistics Providers (3PLs)
• Food & Beverage
• Pharmaceuticals & Healthcare
• Consumer Goods
• Industrial & Manufacturing
• Others

By Deployment Mode

• On-Premises
• Cloud-Integrated Edge Systems

By Autonomy Level

• Semi-Autonomous Robots
• Fully Autonomous Robots

By Region

• North America
• The U.S.
• Canada
• Mexico
• Europe
• Western Europe
• The UK
• Germany
• France
• Italy
• Spain
• Rest of Western Europe
• Eastern Europe
• Poland
• Russia
• Rest of Eastern Europe
• Asia Pacific
• China
• India
• Japan
• Australia & New Zealand
• South Korea
• ASEAN
• Rest of Asia Pacific
• Middle East & Africa (MEA)
• Saudi Arabia
• South Africa
• UAE
• Rest of MEA
• South America
• Argentina
• Brazil
• Rest of South America

Geography Breakdown

• North America commands a significant 41% share of the global market for AI robotics in warehousing, reflecting the region's proactive approach to addressing critical labor and operational challenges. In both the United States and Canada, the adoption of warehouse robotics is seen as a strategic offensive measure aimed at countering the effects of severe wage inflation and rising labor costs. Warehouse wages in the region have surged beyond $22 per hour, creating substantial pressure on companies to find cost-effective solutions that maintain productivity without escalating expenses. At the same time, warehouses face brutal labor turnover rates exceeding 40%, which disrupts operations and increases recruitment and training costs.
• Within this context, North American supply chain executives are prioritizing solutions that offer more than just inexpensive hardware. Their focus has shifted toward Robotics-as-a-Service (RaaS) models and the seamless integration of advanced software systems. Unlike traditional capital expenditure-heavy investments in robotics equipment, RaaS allows companies to treat automation as an operational expense (OpEx), bypassing the often lengthy and challenging capital expenditure (CapEx) approval processes. This flexibility enables warehouses to rapidly deploy robotic systems and scale operations according to demand without the upfront financial burden.
• As a result, the North American market for AI robotics in warehousing is characterized by sophisticated, flexible approaches that emphasize operational agility and cost management. The region's supply chain leaders are leveraging RaaS and advanced software capabilities to mitigate labor challenges and to enhance overall warehouse efficiency and competitiveness.

Leading Market Participants

• Yaskawa Electric Corporation
• Amazon Robotics
• Boston Dynamics
• Cognex Corporation
• Dematic (KION Group)
• Elettric 80 S.p.A.
• ABB Ltd.
• FANUC Corporation
• Fetch Robotics
• Geek+
• GreyOrange
• KUKA AG
• Locus Robotics
• Magazino GmbH
• Mobile Industrial Robots (MiR)
• Honeywell Intelligrated
• Omron Corporation
• Swisslog (KUKA Group)
• Teradyne Inc. (Adept Technology)

Table of Content

Chapter 1. Executive Summary: Global AI Robotics In Warehousing Market

Chapter 2. Research Methodology & Research Framework

• 2.1. Research Objective
• 2.2. Product Overview
• 2.3. Market Segmentation
• 2.4. Qualitative Research
  • 2.4.1. Primary & Secondary Sources
• 2.5. Quantitative Research
  • 2.5.1. Primary & Secondary Sources
• 2.6. Breakdown of Primary Research Respondents, By Region
• 2.7. Assumption for Study
• 2.8. Market Size Estimation
• 2.9. Data Triangulation

Chapter 3. Global AI Robotics In Warehousing Market Overview

• 3.1. Industry Value Chain Analysis
  • 3.1.1. Component Suppliers
  • 3.1.2. Robotics Manufacturers
  • 3.1.3. Software & AI Solution Providers
  • 3.1.4. System Integrators
  • 3.1.5. End Users
• 3.2. Industry Outlook
  • 3.2.1. Evolution of Warehouse Automation
  • 3.2.2. Adoption Trends of AI in Logistics
• 3.3. PESTLE Analysis
• 3.4. Porter's Five Forces Analysis
  • 3.4.1. Bargaining Power of Suppliers
  • 3.4.2. Bargaining Power of Buyers
  • 3.4.3. Threat of Substitutes
  • 3.4.4. Threat of New Entrants
  • 3.4.5. Degree of Competition
• 3.5. Market Growth and Outlook
  • 3.5.1. Market Revenue Estimates and Forecast (US$ Mn), 2020-2035
  • 3.5.2. Price Trend Analysis

Chapter 4. Global AI Robotics In Warehousing Market Analysis

• 4.1. Competition Dashboard
  • 4.1.1. Market Concentration Rate
  • 4.1.2. Company Market Share Analysis (Value %), 2025
  • 4.1.3. Competitor Mapping & Benchmarking

Chapter 5. Global AI Robotics In Warehousing Market Analysis

• 5.1. Market Dynamics and Trends
  • 5.1.1. Growth Drivers
  • 5.1.2. Restraints
  • 5.1.3. Opportunity
  • 5.1.4. Key Trends
• 5.2. Market Size and Forecast, 2020-2035 (US$ Mn)
  • 5.2.1. By AI Capability
    • 5.2.1.1. Key Insights
      • 5.2.1.1.1. Machine Learning & Predictive Analytics
      • 5.2.1.1.2. Computer Vision & Imaging
      • 5.2.1.1.3. Sensor Fusion & IoT Integration
      • 5.2.1.1.4. Natural Language Processing (NLP)
      • 5.2.1.1.5. Autonomous Navigation & Path Planning
      • 5.2.1.1.6. Others
  • 5.2.2. By Robot Type
    • 5.2.2.1. Key Insights
      • 5.2.2.1.1. Automated Guided Vehicles (AGVs)
        • 5.2.2.1.1.1. Towing AGVs
        • 5.2.2.1.1.2. Unit Load AGVs
      • 5.2.2.1.2. Autonomous Mobile Robots (AMRs)
        • 5.2.2.1.2.1. Picking AMRs
        • 5.2.2.1.2.2. Pallet Handling AMRs
      • 5.2.2.1.3. Robotic Arms & Pick-and-Place Robots
      • 5.2.2.1.4. Collaborative Robots (Cobots)
      • 5.2.2.1.5. Sorting & Packaging Robots
      • 5.2.2.1.6. Others
  • 5.2.3. By Autonomy Level
    • 5.2.3.1. Key Insights
      • 5.2.3.1.1. Semi-Autonomous Robots
      • 5.2.3.1.2. Fully Autonomous Robots
  • 5.2.4. By Deployment Mode
    • 5.2.4.1. Key Insights
      • 5.2.4.1.1. On-Premises
      • 5.2.4.1.2. Cloud-Integrated Edge Systems
  • 5.2.5. By Function / Application
    • 5.2.5.1. Key Insights
      • 5.2.5.1.1. Picking & Packing
      • 5.2.5.1.2. Sorting & Distribution
      • 5.2.5.1.3. Inventory Management & Tracking
      • 5.2.5.1.4. Material Transport & Handling
      • 5.2.5.1.5. Loading & Unloading
      • 5.2.5.1.6. Quality Inspection
      • 5.2.5.1.7. Others
  • 5.2.6. By End User / Industry
    • 5.2.6.1. Key Insights
      • 5.2.6.1.1. E-Commerce & Retail
      • 5.2.6.1.2. Third-Party Logistics Providers (3PLs)
      • 5.2.6.1.3. Food & Beverage
      • 5.2.6.1.4. Pharmaceuticals & Healthcare
      • 5.2.6.1.5. Consumer Goods
      • 5.2.6.1.6. Industrial & Manufacturing
      • 5.2.6.1.7. Others
  • 5.2.7. By Region
    • 5.2.7.1. Key Insights
      • 5.2.7.1.1. North America
        • 5.2.7.1.1.1. The U.S.
        • 5.2.7.1.1.2. Canada
        • 5.2.7.1.1.3. Mexico
      • 5.2.7.1.2. Europe
        • 5.2.7.1.2.1. Western Europe
          • 5.2.7.1.2.1.1. The UK
          • 5.2.7.1.2.1.2. Germany
          • 5.2.7.1.2.1.3. France
          • 5.2.7.1.2.1.4. Italy
          • 5.2.7.1.2.1.5. Spain
          • 5.2.7.1.2.1.6. Rest of Western Europe
        • 5.2.7.1.2.2. Eastern Europe
          • 5.2.7.1.2.2.1. Poland
          • 5.2.7.1.2.2.2. Russia
          • 5.2.7.1.2.2.3. Rest of Eastern Europe
      • 5.2.7.1.3. Asia Pacific
        • 5.2.7.1.3.1. China
        • 5.2.7.1.3.2. India
        • 5.2.7.1.3.3. Japan
        • 5.2.7.1.3.4. South Korea
        • 5.2.7.1.3.5. Australia & New Zealand
        • 5.2.7.1.3.6. ASEAN
          • 5.2.7.1.3.6.1. Indonesia
          • 5.2.7.1.3.6.2. Malaysia
          • 5.2.7.1.3.6.3. Thailand
          • 5.2.7.1.3.6.4. Singapore
          • 5.2.7.1.3.6.5. Rest of ASEAN
        • 5.2.7.1.3.7. Rest of Asia Pacific
      • 5.2.7.1.4. Middle East & Africa
        • 5.2.7.1.4.1. UAE
        • 5.2.7.1.4.2. Saudi Arabia
        • 5.2.7.1.4.3. South Africa
        • 5.2.7.1.4.4. Rest of MEA
      • 5.2.7.1.5. South America
        • 5.2.7.1.5.1. Argentina
        • 5.2.7.1.5.2. Brazil
        • 5.2.7.1.5.3. Rest of South America

Chapter 6. North America Market Analysis

• 6.1. Market Dynamics and Trends
  • 6.1.1. Growth Drivers
  • 6.1.2. Restraints
  • 6.1.3. Opportunity
  • 6.1.4. Key Trends
• 6.2. Market Size and Forecast, 2020-2035 (US$ Mn)
  • 6.2.1. Key Insights
    • 6.2.1.1. By AI Capability
    • 6.2.1.2. By Robot Type
    • 6.2.1.3. By Autonomy Level
    • 6.2.1.4. By Deployment Mode
    • 6.2.1.5. By Function / Application
    • 6.2.1.6. By End User / Industry
    • 6.2.1.7. By Country

Chapter 7. Europe Market Analysis

• 7.1. Market Dynamics and Trends
  • 7.1.1. Growth Drivers
  • 7.1.2. Restraints
  • 7.1.3. Opportunity
  • 7.1.4. Key Trends
• 7.2. Market Size and Forecast, 2020-2035 (US$ Mn)
  • 7.2.1. Key Insights
    • 7.2.1.1. By AI Capability
    • 7.2.1.2. By Robot Type
    • 7.2.1.3. By Autonomy Level
    • 7.2.1.4. By Deployment Mode
    • 7.2.1.5. By Function / Application
    • 7.2.1.6. By End User / Industry
    • 7.2.1.7. By Country

Chapter 8. Asia Pacific Market Analysis

• 8.1. Market Dynamics and Trends
  • 8.1.1. Growth Drivers
  • 8.1.2. Restraints
  • 8.1.3. Opportunity
  • 8.1.4. Key Trends
• 8.2. Market Size and Forecast, 2020-2035 (US$ Mn)
  • 8.2.1. Key Insights
    • 8.2.1.1. By AI Capability
    • 8.2.1.2. By Robot Type
    • 8.2.1.3. By Autonomy Level
    • 8.2.1.4. By Deployment Mode
    • 8.2.1.5. By Function / Application
    • 8.2.1.6. By End User / Industry
    • 8.2.1.7. By Country

Chapter 9. Middle East & Africa Market Analysis

• 9.1. Market Dynamics and Trends
  • 9.1.1. Growth Drivers
  • 9.1.2. Restraints
  • 9.1.3. Opportunity
  • 9.1.4. Key Trends
• 9.2. Market Size and Forecast, 2020-2035 (US$ Mn)
  • 9.2.1. Key Insights
    • 9.2.1.1. By AI Capability
    • 9.2.1.2. By Robot Type
    • 9.2.1.3. By Autonomy Level
    • 9.2.1.4. By Deployment Mode
    • 9.2.1.5. By Function / Application
    • 9.2.1.6. By End User / Industry
    • 9.2.1.7. By Country

Chapter 10. South America Market Analysis

• 10.1. Market Dynamics and Trends
  • 10.1.1. Growth Drivers
  • 10.1.2. Restraints
  • 10.1.3. Opportunity
  • 10.1.4. Key Trends
• 10.2. Market Size and Forecast, 2020-2035 (US$ Mn)
  • 10.2.1. Key Insights
    • 10.2.1.1. By AI Capability
    • 10.2.1.2. By Robot Type
    • 10.2.1.3. By Autonomy Level
    • 10.2.1.4. By Deployment Mode
    • 10.2.1.5. By Function / Application
    • 10.2.1.6. By End User / Industry
    • 10.2.1.7. By Country

Chapter 11. Company Profile (Company Overview, Financial Matrix, Key Product landscape, Key Personnel, Key Competitors, Contact Address, and Business Strategy Outlook)

• 11.1. Yaskawa Electric Corporation
• 11.2. Amazon Robotics
• 11.3. Boston Dynamics
• 11.4. Cognex Corporation
• 11.5. Dematic (KION Group)
• 11.6. Elettric 80 S.p.A.
• 11.7. ABB Ltd.
• 11.8. FANUC Corporation
• 11.9. Fetch Robotics
• 11.10. Geek+
• 11.11. GreyOrange
• 11.12. KUKA AG
• 11.13. Locus Robotics
• 11.14. Magazino GmbH
• 11.15. Mobile Industrial Robots (MiR)
• 11.16. Honeywell Intelligrated
• 11.17. Omron Corporation
• 11.18. Swisslog (KUKA Group)
• 11.19. Teradyne Inc. (Adept Technology)
• 11.20. Other Prominent Players

Chapter 12. Annexure

• 12.1. List of Secondary Sources
• 12.2. Key Country Markets- Macro Economic Outlook/Indicators