Growing Automation In Logistics Fueling The Growth Of The Market Due To Increasing Efficiency And Cost Reduction: Transformative Forces Shaping the Machine Learning in Supply Chain Management Market Landscape in 2025

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How Large Will the Machine Learning in Supply Chain Management Market Size By 2025?
The market size for machine learning in supply chain management has seen impressive growth recently. It is projected to increase from $8.32 billion in 2024 to $10.26 billion in 2025, showing a compound annual growth rate (CAGR) of 23.3%. The expansion during the historic period can be credited to a surge in operational efficiency, the need for predictive analytics, the trend of automation in logistics, an increase in data-powered decision making, and enhanced accuracy in predicting demand.

How Big Is the Machine Learning in Supply Chain Management Market Size Expected to Grow by 2029?
Expectations are high for substantial growth in the machine learning in supply chain management market size over the next few years, with projections reaching $23.98 billion in 2029 at a compound annual growth rate (CAGR) of 23.6%. The anticipated growth in this period can be pegged to factors like the adoption of digital transformation, spiking market fluctuations, a strong focus on sustainability, a surge in e-commerce, the increased importance of data-driven decisions, and the growing demand for automation and data-informed decision-making in logistics. As we look ahead, key trends for this forecast period encompass improved inventory management solutions, real-time visibility of supply chains, AI-driven risk management, cloud-centered supply chain solutions to boost collaboration, and AI-enabled warehouse optimization strategies.

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Which Key Market Drivers Powering Machine Learning in Supply Chain Management Market Expansion and Growth?
The surge in automation within the logistics sector is predicted to boost the expansion of the machine learning market in supply chain management. The term "automation in logistics" relates to the implementation of technologies like robotics, AI, and software systems for the purpose of optimizing supply chain processes with limited human interaction. The rising trend towards logistics automation can be attributed to its capacity to enhance efficiency, curb expenses, and satisfy increasing e-commerce needs via the application of technology to upscale operational capabilities and customer contentment. The application of machine learning in supply chain management supports predictive analytics, demand predictions, and real-time decision making. It also propels automation of logistics through improving route management, warehouse robotics, and smart inventory management. For example, as per data from the International Federation of Robotics (IFR), a Germany-based trade alliance, in 2023, the global count of operational robots within factories was reported as 4,281,585 units. This represented a 10% rise from the 3,904,000 units registered in 2022. As such, the increasing embrace of automation within logistics is fueling the market growth for machine learning in supply chain management.

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Which Fast-Growing Trends Are Poised to Disrupt the Machine Learning in Supply Chain Management Market?
In the machine learning in supply chain management market, leading companies are directing their attention towards creating technologically superior solutions. These include artificial intelligence (AI) assistants for supply chain management aiming to enrich decision-making, streamline operations, and boost overall performance. An AI assistant in this context is a smart software tool that leverages artificial intelligence for supply chain process automation and optimization, covering activities like forecasting, inventory management and logistics planning. In February 2024, for instance, One Network Enterprises, a US-based digital supply chain solutions provider, launched NEO Assistant, a revolutionary AI tool specifically designed for supply chain management. This pioneering platform makes use of both AI and machine learning (ML) to offer real-time monitoring, intelligent prescriptions, and interactive visualizations. By fusing AI-generated insights with ML-driven predictive analytics, NEO Assistant improves decision-making and functional effectiveness across intricate logistic networks. Users will benefit from actionable suggestions and efficient troubleshooting, which makes it extremely useful in managing dynamic supply chain settings.

What Are the Emerging Segments in the Machine Learning in Supply Chain Management Market?
The machine learning in supply chain managementmarket covered in this report is segmented -

1) By Component: Software, Services
2) By Technology: Artificial Intelligence, Deep Learning, Natural Language Processing, Predictive Analytics
3) By Deployment Mode: Cloud-Based, On-Premises
4) By Application: Demand Forecasting, Inventory Management, Supplier Selection, Logistics Optimization, Risk Management
5) By End-User: Retail And E-Commerce, Manufacturing, Healare, Automotive, Food And Beverage, Consumer Goods, Other End-Users

Subsegments:
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
2) By Services: Managed Services, Professional Services, Consulting Services, Training And Support Services

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Who Are the Global Leaders in the Machine Learning in Supply Chain Management Market?
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.

Which are the Top Profitable Regional Markets for the Machine Learning in Supply Chain Management Industry?
North America was the largest region in the machine learning in supply chain management market in 2024. The regions covered in the machine learning in supply chain management market report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.

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