The global AI in warehousing market size was valued at USD 11.22 billion in 2024 and is projected to reach USD 45.12 billion by 2030, growing at a CAGR of 26.1% from 2025 to 2030. The rapid expansion of e-commerce, which requires faster and more accurate order fulfillment, is a major driver of this growth.
Warehouses face increasing pressure to manage larger volumes and more complex inventories, prompting the adoption of AI-driven automation, robotics, and advanced analytics. These technologies streamline operations, reduce manual errors, and enhance inventory management, while also addressing labor shortages and rising operational costs. AI integration enables real-time decision-making, improves productivity, and boosts warehouse efficiency and competitiveness. For example, Ocado operates highly advanced AI-driven warehouses where robotic systems, coordinated by AI, manage storage, retrieval, and packing with remarkable speed and precision.
Continuous innovations in robotics, machine learning, and big data analytics are making AI solutions more accessible and scalable for warehouses of all sizes. Integrating AI with IoT devices allows real-time monitoring and management of inventory and assets, enhancing visibility and supply chain decision-making. Companies are investing in research and development to optimize warehouse workflows, automate repetitive tasks, and support predictive maintenance. AI-powered computer vision and robotic systems further improve operational accuracy by detecting misplaced or damaged goods, reducing human error, and streamlining inventory processes.
Sustainability and cost-efficiency are also influencing AI adoption in warehousing. AI solutions help optimize energy consumption, minimize waste, and improve resource allocation, aligning with corporate sustainability goals. As businesses strive to enhance performance metrics and meet evolving customer expectations, AI adoption in warehousing is transforming traditional logistics into data-driven, agile, and highly efficient operations.
Key Market Highlights:
- North America dominated the AI in warehousing market in 2024, accounting for a revenue share of over 32%.
- By component, the hardware segment led the market in 2024 with more than 59% of global revenue.
- By application, the inventory management segment held the largest share in 2024.
- By deployment, the cloud segment was the market leader in 2024.
- By organization size, large enterprises dominated the market in 2024.
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Market Performance:
- 2024 Market Size: USD 11.22 Billion
- 2030 Projected Market Size: USD 45.12 Billion
- CAGR (2025-2030): 26.1%
- North America: Largest market in 2024
- Asia Pacific: Fastest-growing region
Prominent Companies & Market Dynamics:
Key players in the AI in warehousing market include ABB, Google LLC, Honeywell International, Inc., and IBM Corporation.
- ABB focuses on electrification, automation, and robotics, integrating AI into warehouse operations. Its AI-powered solutions improve warehouse efficiency through intelligent robotics, automated material handling, and advanced process optimization. ABB uses machine learning and analytics to enhance inventory management, optimize picking and sorting, and enable predictive maintenance.
- Honeywell International, Inc. provides advanced automation, robotics, and data-driven solutions for modern distribution centers. Through its Honeywell Robotics Center and partnerships with companies like Google Cloud, Honeywell develops AI and machine learning applications that automate routine tasks, streamline workflows, and provide real-time operational insights.
Key Companies:
- ABB
- Amazon Web Services, Inc.
- Google LLC
- Honeywell International, Inc.
- IBM Corporation
- Microsoft
- Oracle
- SAP SE
- Siemens AG
- Zebra Technologies Corporation
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Conclusion:
The AI in warehousing market is set for robust growth, driven by the rising demand for faster, more accurate, and cost-effective operations. Continuous advancements in AI, robotics, and analytics, along with investments by key market players, are enabling warehouses to become more automated, data-driven, and sustainable, transforming the logistics landscape.
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