창고용 AI 시장 규모, 점유율, 성장 및 세계 산업 분석 : 유형별, 용도별, 지역별 인사이트 및 예측(2024-2032년)

Growth Factors of AI in warehousing Market

The global AI in warehousing market is undergoing a strong transformation as businesses adopt advanced technologies to automate storage, movement, and inventory operations. According to the latest findings, the market was valued at USD 10.27 billion in 2024, driven by rapid digitalization across industries and the need for faster, more efficient warehouse processes. The market is projected to increase to USD 12.69 billion in 2025, supported by rising investments in robotics, predictive analytics, and AI-driven warehouse management systems. By 2032, the market is expected to reach USD 61.36 billion, reflecting strong long-term adoption of intelligent automation and AI-powered logistics systems.

AI Transforming Warehouse Operations

AI technologies have become core components of next-generation warehouse operations. In 2024, companies increasingly deployed AI-powered tools for inventory management, supply chain visibility, order picking, sorting, predictive maintenance, and routing optimization. Real-time analytics offered by AI systems enabled warehouse managers to track shipments, monitor stock levels, and evaluate performance metrics instantly, improving decision-making and operational accuracy. The ability to minimize human error and reduce manual dependency contributed significantly to the expansion of AI solutions across large and mid-sized warehouses.

Leading global vendors-including Amazon Web Services, Honeywell, IBM, Oracle, Microsoft, and Locus Robotics-strengthened their presence through collaborations with warehousing companies. These partnerships allowed tech providers to integrate AI algorithms, robotic systems, and cloud solutions into warehouse workflows, making operations more scalable and increasing overall productivity in both 2024 and 2025.

Impact of Reciprocal Tariffs

Despite strong demand, market growth faces challenges due to tariff-related disruptions. Many AI-enabled components-such as IoT sensors, robotic systems, and warehouse management software-are sourced from the U.S., China, Japan, and South Korea. Tariffs imposed under the Trump administration have the potential to raise import costs for critical components. These higher expenses particularly impact small businesses with limited capital, slowing down AI adoption and delaying investments in next-generation warehouse automation. As a result, tariff barriers remain a notable challenge for AI deployment in 2024 and 2025.

Market Dynamics

Drivers: Rising AI Adoption in Retail and E-commerce

The rapid expansion of the online retail sector continues to be a major driver. As e-commerce volumes grow, warehouses face increasing pressure to deliver fast, accurate order fulfillment. AI technologies significantly improve operational speed, reduce manual errors, and offer substantial cost savings. According to industry data, 56% of businesses had integrated AI into at least one functional area in 2023, with adoption expected to rise further across global retail chains.

Restraints: High Initial Investment

The high cost of robotics, sensors, AI software, and integration services remains a barrier for SMEs. Upgrading existing infrastructure to support AI adoption requires major capital investments, limiting the adoption of advanced automation tools among smaller warehouses.

Opportunities: Surge in Predictive Maintenance

AI-driven predictive maintenance is creating strong opportunities, reducing downtime by 30-50%, extending equipment life by 17-20%, and lowering maintenance costs by 7-10%. These benefits are expected to accelerate the adoption of predictive analytics across global warehouses.

Key Trends: Rapid Growth of Autonomous Robots

A major trend reshaping the market is the rising deployment of autonomous robots. An industry survey suggests that 4 million robots are expected to be installed across 50,000 warehouses by 2025. These robots support accurate inventory tracking, gentle handling of fragile goods, and faster picking and packing operations, significantly improving warehouse productivity.

Regional Outlook

North America

North America led the market with 36.71% share in 2024, supported by advanced digital infrastructure and large-scale automation investments. The U.S. continues to adopt AI for retail, logistics, manufacturing, and food sectors, particularly due to ongoing labor shortages.

Asia Pacific

Asia Pacific is expected to grow at the highest CAGR through 2032, driven by major warehousing expansions in India, China, Vietnam, and Indonesia. India's warehouse capacity is expected to double by 2027, highlighting strong future demand.

Europe, Middle East & Africa, South America

Europe faces labor shortages, accelerating AI adoption, while the Middle East invests heavily in smart logistics hubs. South America shows rising adoption led by Brazil, Argentina, and Chile.

Conclusion

With the market increasing from USD 10.27 billion in 2024 to USD 61.36 billion by 2032, AI in warehousing is positioned to become one of the most transformative technologies in global logistics. Innovations in robotics, predictive analytics, and cloud-based AI platforms will continue driving efficiency, visibility, and automation in warehouse operations worldwide.

Segmentation By Component

• Hardware
• Software
• Services

By Deployment

• On-premises
• Cloud

By Application

• Inventory Management
• Order Picking & Sorting
• Warehouse Optimization
• Predictive Maintenance
• Supply Chain Visibility

By Industry

• Logistics & Transportation
• Retail & E-commerce
• Food & Beverage
• Manufacturing
• Healthcare
• Others (Energy & Utilities)

By Region

• North America (By Component, By Deployment, By Application, By Industry, and By Country)
  • U.S.
  • Canada
  • Mexico
• South America (By Component, By Deployment, By Application, By Industry, and By Country)
  • Brazil
  • Argentina
  • Rest of South America
• Europe (By Component, By Deployment, By Application, By Industry, and By Country)
  • U.K.
  • Germany
  • France
  • Italy
  • Spain
  • Russia
  • Benelux
  • Nordics
  • Rest of Europe
• Middle East & Africa (By Component, By Deployment, By Application, By Industry, and By Country)
  • Turkey
  • Israel
  • GCC
  • North Africa
  • South Africa
  • Rest of Middle East & Africa
• Asia Pacific (By Component, By Deployment, By Application, By Industry, and By Country)
  • China
  • India
  • Japan
  • South Korea
  • ASEAN
  • Oceania
  • Rest of Asia Pacific

Companies Profiled in the Report * Zoom Communications, Inc. (U.S.)

• BigMarker (U.S.)
• Cvent Inc. (U.S.)
• Hubilo Technologies Inc. (U.S.)
• Zoho Corporation Pvt. Ltd. (India)
• Remo (U.S.)
• vFairs (U.S.)
• EventMobi (Canada)
• 6Connex (U.S.)
• Microsoft Corporation (U.S.)

Table of Content

1. Introduction

• 1.1. Definition, By Segment
• 1.2. Research Methodology/Approach
• 1.3. Data Sources

2. Executive Summary

3. Market Dynamics

• 3.1. Macro and Micro Economic Indicators
• 3.2. Drivers, Restraints, Opportunities and Trends
• 3.3. Impact of Reciprocal Tariff

4. Competition Landscape

• 4.1. Business Strategies Adopted by Key Players
• 4.2. Consolidated SWOT Analysis of Key Players
• 4.3. Global AI in Warehousing Key Players (Top 3 - 5) Market Share/Ranking, 2024

5. Global AI in Warehousing Market Size Estimates and Forecasts, By Segments, 2019-2032

• 5.1. Key Findings
• 5.2. By Component (USD)
  • 5.2.1. Hardware
  • 5.2.2. Software
  • 5.2.3. Services
• 5.3. By Deployment (USD)
  • 5.3.1. On-premises
  • 5.3.2. Cloud
• 5.4. By Application (USD)
  • 5.4.1. Inventory Management
  • 5.4.2. Order Picking & Sorting
  • 5.4.3. Warehouse Optimization
  • 5.4.4. Predictive Maintenance
  • 5.4.5. Supply Chain Visibility
• 5.5. By Industry (USD)
  • 5.5.1. Logistics & Transportation
  • 5.5.2. Retail & E-commerce
  • 5.5.3. Food & Beverage
  • 5.5.4. Manufacturing
  • 5.5.5. Healthcare
  • 5.5.6. Others (Energy & Utilities, etc.)
• 5.6. By Region (USD)
  • 5.6.1. North America
  • 5.6.2. South America
  • 5.6.3. Europe
  • 5.6.4. Middle East & Africa
  • 5.6.5. Asia Pacific

6. North America AI in Warehousing Market Size Estimates and Forecasts, By Segments, 2019-2032

• 6.1. Key Findings
• 6.2. By Component (USD)
  • 6.2.1. Hardware
  • 6.2.2. Software
  • 6.2.3. Services
• 6.3. By Deployment (USD)
  • 6.3.1. On-premises
  • 6.3.2. Cloud
• 6.4. By Application (USD)
  • 6.4.1. Inventory Management
  • 6.4.2. Order Picking & Sorting
  • 6.4.3. Warehouse Optimization
  • 6.4.4. Predictive Maintenance
  • 6.4.5. Supply Chain Visibility
• 6.5. By Industry (USD)
  • 6.5.1. Logistics & Transportation
  • 6.5.2. Retail & E-commerce
  • 6.5.3. Food & Beverage
  • 6.5.4. Manufacturing
  • 6.5.5. Healthcare
  • 6.5.6. Others (Energy & Utilities, etc.)
• 6.6. By Country (USD)
  • 6.6.1. United States
  • 6.6.2. Canada
  • 6.6.3. Mexico

7. South America AI in Warehousing Market Size Estimates and Forecasts, By Segments, 2019-2032

• 7.1. Key Findings
• 7.2. By Component (USD)
  • 7.2.1. Hardware
  • 7.2.2. Software
  • 7.2.3. Services
• 7.3. By Deployment (USD)
  • 7.3.1. On-premises
  • 7.3.2. Cloud
• 7.4. By Application (USD)
  • 7.4.1. Inventory Management
  • 7.4.2. Order Picking & Sorting
  • 7.4.3. Warehouse Optimization
  • 7.4.4. Predictive Maintenance
  • 7.4.5. Supply Chain Visibility
• 7.5. By Industry (USD)
  • 7.5.1. Logistics & Transportation
  • 7.5.2. Retail & E-commerce
  • 7.5.3. Food & Beverage
  • 7.5.4. Manufacturing
  • 7.5.5. Healthcare
  • 7.5.6. Others (Energy & Utilities, etc.)
• 7.6. By Country (USD)
  • 7.6.1. Brazil
  • 7.6.2. Argentina
  • 7.6.3. Rest of South America

8. Europe AI in Warehousing Market Size Estimates and Forecasts, By Segments, 2019-2032

• 8.1. Key Findings
• 8.2. By Component (USD)
  • 8.2.1. Hardware
  • 8.2.2. Software
  • 8.2.3. Services
• 8.3. By Deployment (USD)
  • 8.3.1. On-premises
  • 8.3.2. Cloud
• 8.4. By Application (USD)
  • 8.4.1. Inventory Management
  • 8.4.2. Order Picking & Sorting
  • 8.4.3. Warehouse Optimization
  • 8.4.4. Predictive Maintenance
  • 8.4.5. Supply Chain Visibility
• 8.5. By Industry (USD)
  • 8.5.1. Logistics & Transportation
  • 8.5.2. Retail & E-commerce
  • 8.5.3. Food & Beverage
  • 8.5.4. Manufacturing
  • 8.5.5. Healthcare
  • 8.5.6. Others (Energy & Utilities, etc.)
• 8.6. By Country (USD)
  • 8.6.1. United Kingdom
  • 8.6.2. Germany
  • 8.6.3. France
  • 8.6.4. Italy
  • 8.6.5. Spain
  • 8.6.6. Russia
  • 8.6.7. Benelux
  • 8.6.8. Nordics
  • 8.6.9. Rest of Europe

9. Middle East & Africa AI in Warehousing Market Size Estimates and Forecasts, By Segments, 2019-2032

• 9.1. Key Findings
• 9.2. By Component (USD)
  • 9.2.1. Hardware
  • 9.2.2. Software
  • 9.2.3. Services
• 9.3. By Deployment (USD)
  • 9.3.1. On-premises
  • 9.3.2. Cloud
• 9.4. By Application (USD)
  • 9.4.1. Inventory Management
  • 9.4.2. Order Picking & Sorting
  • 9.4.3. Warehouse Optimization
  • 9.4.4. Predictive Maintenance
  • 9.4.5. Supply Chain Visibility
• 9.5. By Industry (USD)
  • 9.5.1. Logistics & Transportation
  • 9.5.2. Retail & E-commerce
  • 9.5.3. Food & Beverage
  • 9.5.4. Manufacturing
  • 9.5.5. Healthcare
  • 9.5.6. Others (Energy & Utilities, etc.)
• 9.6. By Country (USD)
  • 9.6.1. Turkey
  • 9.6.2. Israel
  • 9.6.3. GCC
  • 9.6.4. North Africa
  • 9.6.5. South Africa
  • 9.6.6. Rest of MEA

10. Asia Pacific AI in Warehousing Market Size Estimates and Forecasts, By Segments, 2019-2032

• 10.1. Key Findings
• 10.2. By Component (USD)
  • 10.2.1. Hardware
  • 10.2.2. Software
  • 10.2.3. Services
• 10.3. By Deployment (USD)
  • 10.3.1. On-premises
  • 10.3.2. Cloud
• 10.4. By Application (USD)
  • 10.4.1. Inventory Management
  • 10.4.2. Order Picking & Sorting
  • 10.4.3. Warehouse Optimization
  • 10.4.4. Predictive Maintenance
  • 10.4.5. Supply Chain Visibility
• 10.5. By Industry (USD)
  • 10.5.1. Logistics & Transportation
  • 10.5.2. Retail & E-commerce
  • 10.5.3. Food & Beverage
  • 10.5.4. Manufacturing
  • 10.5.5. Healthcare
  • 10.5.6. Others (Energy & Utilities, etc.)
• 10.6. By Country (USD)
  • 10.6.1. China
  • 10.6.2. India
  • 10.6.3. Japan
  • 10.6.4. South Korea
  • 10.6.5. ASEAN
  • 10.6.6. Oceania
  • 10.6.7. Rest of Asia Pacific

11. Company Profiles for Top 10 Players (Based on data availability in public domain and/or on paid databases)

• 11.1.
  • 11.1.1. Amazon Web Services, Inc.
    • 11.1.1.1. Overview
      • 11.1.1.1.1. Key Management
      • 11.1.1.1.2. Headquarters
      • 11.1.1.1.3. Offerings/Business Segments
    • 11.1.1.2. Key Details (Key details are consolidated data and not product/service specific)
      • 11.1.1.2.1. Employee Size
      • 11.1.1.2.2. Past and Current Revenue
      • 11.1.1.2.3. Geographical Share
      • 11.1.1.2.4. Business Segment Share
      • 11.1.1.2.5. Recent Developments
  • 11.1.2. Alphabet Inc. (Google LLC)
    • 11.1.2.1. Overview
      • 11.1.2.1.1. Key Management
      • 11.1.2.1.2. Headquarters
      • 11.1.2.1.3. Offerings/Business Segments
    • 11.1.2.2. Key Details (Key details are consolidated data and not product/service specific)
      • 11.1.2.2.1. Employee Size
      • 11.1.2.2.2. Past and Current Revenue
      • 11.1.2.2.3. Geographical Share
      • 11.1.2.2.4. Business Segment Share
      • 11.1.2.2.5. Recent Developments
  • 11.1.3. Honeywell International, Inc.
    • 11.1.3.1. Overview
      • 11.1.3.1.1. Key Management
      • 11.1.3.1.2. Headquarters
      • 11.1.3.1.3. Offerings/Business Segments
    • 11.1.3.2. Key Details (Key details are consolidated data and not product/service specific)
      • 11.1.3.2.1. Employee Size
      • 11.1.3.2.2. Past and Current Revenue
      • 11.1.3.2.3. Geographical Share
      • 11.1.3.2.4. Business Segment Share
      • 11.1.3.2.5. Recent Developments
  • 11.1.4. IBM Corporation
    • 11.1.4.1. Overview
      • 11.1.4.1.1. Key Management
      • 11.1.4.1.2. Headquarters
      • 11.1.4.1.3. Offerings/Business Segments
    • 11.1.4.2. Key Details (Key details are consolidated data and not product/service specific)
      • 11.1.4.2.1. Employee Size
      • 11.1.4.2.2. Past and Current Revenue
      • 11.1.4.2.3. Geographical Share
      • 11.1.4.2.4. Business Segment Share
      • 11.1.4.2.5. Recent Developments
  • 11.1.5. Oracle Corporation
    • 11.1.5.1. Overview
      • 11.1.5.1.1. Key Management
      • 11.1.5.1.2. Headquarters
      • 11.1.5.1.3. Offerings/Business Segments
    • 11.1.5.2. Key Details (Key details are consolidated data and not product/service specific)
      • 11.1.5.2.1. Employee Size
      • 11.1.5.2.2. Past and Current Revenue
      • 11.1.5.2.3. Geographical Share
      • 11.1.5.2.4. Business Segment Share
      • 11.1.5.2.5. Recent Developments
  • 11.1.6. Locus Robotics
    • 11.1.6.1. Overview
      • 11.1.6.1.1. Key Management
      • 11.1.6.1.2. Headquarters
      • 11.1.6.1.3. Offerings/Business Segments
    • 11.1.6.2. Key Details (Key details are consolidated data and not product/service specific)
      • 11.1.6.2.1. Employee Size
      • 11.1.6.2.2. Past and Current Revenue
      • 11.1.6.2.3. Geographical Share
      • 11.1.6.2.4. Business Segment Share
      • 11.1.6.2.5. Recent Developments
  • 11.1.7. Zebra Technologies Corporation
    • 11.1.7.1. Overview
      • 11.1.7.1.1. Key Management
      • 11.1.7.1.2. Headquarters
      • 11.1.7.1.3. Offerings/Business Segments
    • 11.1.7.2. Key Details (Key details are consolidated data and not product/service specific)
      • 11.1.7.2.1. Employee Size
      • 11.1.7.2.2. Past and Current Revenue
      • 11.1.7.2.3. Geographical Share
      • 11.1.7.2.4. Business Segment Share
      • 11.1.7.2.5. Recent Developments
  • 11.1.8. SAP SE
    • 11.1.8.1. Overview
      • 11.1.8.1.1. Key Management
      • 11.1.8.1.2. Headquarters
      • 11.1.8.1.3. Offerings/Business Segments
    • 11.1.8.2. Key Details (Key details are consolidated data and not product/service specific)
      • 11.1.8.2.1. Employee Size
      • 11.1.8.2.2. Past and Current Revenue
      • 11.1.8.2.3. Geographical Share
      • 11.1.8.2.4. Business Segment Share
      • 11.1.8.2.5. Recent Developments
  • 11.1.9. Siemens AG
    • 11.1.9.1. Overview
      • 11.1.9.1.1. Key Management
      • 11.1.9.1.2. Headquarters
      • 11.1.9.1.3. Offerings/Business Segments
    • 11.1.9.2. Key Details (Key details are consolidated data and not product/service specific)
      • 11.1.9.2.1. Employee Size
      • 11.1.9.2.2. Past and Current Revenue
      • 11.1.9.2.3. Geographical Share
      • 11.1.9.2.4. Business Segment Share
      • 11.1.9.2.5. Recent Developments
  • 11.1.10. ABB Ltd.
    • 11.1.10.1. Overview
      • 11.1.10.1.1. Key Management
      • 11.1.10.1.2. Headquarters
      • 11.1.10.1.3. Offerings/Business Segments
    • 11.1.10.2. Key Details (Key details are consolidated data and not product/service specific)
      • 11.1.10.2.1. Employee Size
      • 11.1.10.2.2. Past and Current Revenue
      • 11.1.10.2.3. Geographical Share
      • 11.1.10.2.4. Business Segment Share
      • 11.1.10.2.5. Recent Developments
• 11.2. Key Takeaways