Featuring market attractiveness scoring, total addressable market sizing, company benchmarking matrices, interactive Excel dashboards, deeper supply chain intelligence, emerging startup tracking, and granular product-level insights, The Business Research Company’s 2026 market reports are built to deliver research that is both more actionable and more strategically valuable.
#Machine Learning in Supply Chain Management Market Growth From $12.71 Billion In 2026 To $29.53 Billion By 2030 At A CAGR Of 23.5%#_x000D_
The machine learning in supply chain management market has experienced substantial growth in its size over recent years. It is anticipated to grow from $10.26 billion in 2025 to $12.71 billion in 2026, exhibiting a compound annual growth rate (CAGR) of 23.8%. The historical expansion of this market can be attributed to the rise of global trade networks, the widespread expansion of e-commerce logistics, the adoption of cloud supply chain platforms, an increasing demand for operational efficiency, and the digital transformation occurring in warehouses._x000D_
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The machine learning in supply chain management market size is projected to undergo significant expansion in the upcoming years. It is foreseen to attain a value of $29.53 billion by 2030, growing at a compound annual growth rate (CAGR) of 23.5%. This anticipated growth during the forecast period is fueled by the incorporation of autonomous supply chain systems, the increasing deployment of AI-powered warehouse automation, the adoption of predictive logistics platforms, the rise of real-time data analytics, and heightened investment in smart logistics initiatives. Prominent trends for the forecast horizon include predictive demand forecasting, AI-driven inventory optimization, automated logistics planning, real-time supply chain visibility, and the integration of risk analytics._x000D_
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#Machine Learning in Supply Chain Management Market Expansion Drivers: What’s Shaping Future Growth?#_x000D_
The increasing automation within logistics is anticipated to propel the expansion of the machine learning in supply chain management market moving forward. Automation in logistics involves utilizing technology, such as robotics, AI, and software systems, to streamline and optimize supply chain processes with minimal human intervention. This automation is expanding due to its capacity to boost efficiency, reduce costs, and meet rising e-commerce demands by leveraging technologies to enhance operational scalability and customer satisfaction. Machine learning improves supply chain management by enabling predictive analytics, demand forecasting, and real-time decision-making. It also drives logistics automation through route optimization, warehouse robotics, and intelligent inventory control. For instance, in September 2024, according to the International Federation of Robotics (IFR), a Germany-based industry association, in 2023, the number of robots operating in factories worldwide reached 4,281,585 units, marking a 10% increase from the 3,904,000 units recorded in 2022. Consequently, the growing automation in logistics is driving the growth of the machine learning in supply chain management market._x000D_
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#Machine Learning in Supply Chain Management Market Segmentation And Category Overview#_x000D_
The machine learning in supply chain management market covered in this report is segmented – _x000D_
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1) By Component: Software, Services_x000D_
2) By Technology: Artificial Intelligence, Deep Learning, Natural Language Processing, Predictive Analytics_x000D_
3) By Deployment Mode: Cloud-Based, On-Premises_x000D_
4) By Application: Demand Forecasting, Inventory Management, Supplier Selection, Logistics Optimization, Risk Management_x000D_
5) By End-User: Retail And E-Commerce, Manufacturing, Healthcare, Automotive, Food And Beverage, Consumer Goods, Other End-Users_x000D_
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Subsegments:_x000D_
1) By Software: Demand Forecasting Software, Warehouse Management Software (WMS), Transportation Management Systems (TMS), Inventory Optimization Software, Procurement And Sourcing Analytics Tools, Supply Chain Planning Software, Risk Management And Compliance Software_x000D_
2) By Services: Managed Services, Professional Services, Consulting Services, Training And Support Services_x000D_
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#Machine Learning in Supply Chain Management Market Strategic Trends: What Defines The Next Growth Phase?#_x000D_
Leading firms within the machine learning in supply chain management market are concentrating their efforts on creating sophisticated technological solutions, notably artificial intelligence (AI) assistants designed for supply chain management, with the goal of improving decision-making, streamlining operations, and boosting overall effectiveness. Such an AI assistant functions as a smart software instrument that leverages artificial intelligence to automate and refine various supply chain activities, including forecasting, managing inventory, and planning logistics. An illustrative example occurred in February 2024 when One Network Enterprises, a US-based provider of digital supply chain solutions, unveiled NEO Assistant, an innovative AI tool specifically crafted for supply chain management. This cutting-edge platform utilizes both AI and machine learning (ML) technologies to deliver capabilities such as real-time monitoring, intelligent recommendations, and engaging visualizations. Through the integration of AI-powered insights and ML-driven predictive analytics, NEO Assistant elevates decision-making and operational efficiency throughout intricate logistics networks. The system furnishes users with practical recommendations and simplified problem-solving functionalities, proving exceptionally effective in managing fluid supply chain settings._x000D_
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#Machine Learning in Supply Chain Management Market Competitive Analysis Of Leading Industry Participants#_x000D_
Major companies operating in the machine learning in supply chain management market are Amazon.com Inc., Microsoft Corporation, Deutsche Post AG, FedEx Corporation, Mærsk A/S, Siemens AG, International Business Machines Corporation, Oracle Corporation, SAP SE, Ferguson Enterprises LLC, Zoetop Business Co. Ltd., H&M Hennes & Mauritz AB, J. C. Penney Corporation Inc., ALTANA AG, Koch Industries Inc., Industria de Diseño Textil S.A., FourKites Inc., Noodle.AI Inc., Lokad SAS, Garvis Inc., Logility Inc. _x000D_
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#Machine Learning in Supply Chain Management Market Regional Breakdown: Where Is Demand Concentrated?#_x000D_
North America was the largest region in the machine learning in supply chain management market in 2025. The regions covered in the machine learning in supply chain management market report are Asia-Pacific, South East Asia, Western Europe, Eastern Europe, North America, South America, Middle East, Africa._x000D_
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Wasay has over a decade of experience in market research, data modelling, and analytics, with prior experience at GlobalData and Decision Tree Consulting Services. At The Business Research Company , he leads research operations across syndicated studies, customized consulting engagements, and the Global Market Model platform. His professional experience includes supporting organizations such as Boston Consulting Group, KPMG, and Ernst & Young. Wasay holds a degree in Electronics and Communications Engineering, postgraduate management qualifications from International Management Institute Belgium and Indian School of Business and Entrepreneurship, and completed the Integrated Program in Business Analytics from Indian Institute of Management Indore.
