Predictive Analytics and AI: Shaping the Next Generation of Supply Chains

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AI in Supply Chain Market by Offering (Hardware, Software, Other), Technology (ML, NLP, RPA, Other), Deployment Mode, Application (Demand Forecasting, Other), End-use Industry (Manufacturing, Retail, F&B, Other) & Geography—Forecasts to 2031

According to a new market research report titled, AI in Supply Chain Market by Offering (Hardware, Software, Other), Technology (ML, NLP, RPA, Other), Deployment Mode, Application (Demand Forecasting, Other), End-use Industry (Manufacturing, Retail, F&B, Other) & Geography—Forecasts to 2031’, the AI in supply chain market is projected to reach $58.55 billion by 2031, at a CAGR of 40.4% from 2024 to 2031.

 

The adoption of artificial intelligence in the supply chain is launching a new era of industrial transformation. AI allows companies to automate tasks, forecast demand, optimize routes, manage inventory, and even monitor security, compliance, and other supply chain tasks. In addition, AI is used to optimize inventory management, reduce waste, and conserve resources by ensuring that the right products are in the right place at the right time.

Some of the factors driving the growth of this market are the increasing incorporation of artificial intelligence in supply chain operations and the rising need for greater visibility & transparency in supply chain processes. However, the high procurement & operating costs of AI-based supply chain solutions and the lack of supporting infrastructure restrain the growth of this market.

The AI in supply chain market is segmented by offering (hardware (processors, networking, and storage), software, and services (deployment & integration services, connectivity services, support & maintenance services, and consulting services)), technology (machine learning, computer vision, natural language processing, context-aware computing, and robotic process automation), deployment mode (cloud-based deployments and on-premise deployments), application (demand forecasting, supply chain planning, warehouse management, fleet management, risk management, inventory management, predictive maintenance, real-time supply chain visibility, and other applications), end-use industry (manufacturing, food and beverage, healthcare & pharmaceuticals, automotive, retail, building & construction, medical devices & consumables, aerospace & defense, and other end-use industries). The study also evaluates industry competitors and analyses the market at the regional and country levels.

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Based on offering, the AI in supply chain market is segmented into hardware, software, and services. In 2024, the hardware segment is expected to account for the largest share of 44.4% of the AI in supply chain market. The large market share of this segment is attributed to advancements in data center capabilities, the growing need for storage hardware due to increasing storage requirements for AI applications, the crucial need for constant connectivity in the supply chain operations, and the emphasis on product development and enhancement by manufacturers. For instance, in January 2023, Intel Corporation launched its 4th Gen Intel Xeon Scalable processors (code-named Sapphire Rapids), the Intel Xeon CPU Max Series (code-named Sapphire Rapids HBM), and the Intel Data Center GPU Max Series (code-named Ponte Vecchio). These new processors deliver significant improvements in data center performance, efficiency, security, and AI capabilities.

Based on technology, the AI in supply chain market is segmented into machine learning, computer vision, natural language processing, context-aware computing, and robotic process automation. In 2024, the machine learning segment is expected to account for the largest share of 63.0% of the AI in supply chain market. The large market share of this segment is attributed to the advancements in data center capabilities, increasing deployment of machine learning solutions and its ability to perform tasks without relying on human input, and the rapid adoption of cloud-based technology across several industries. For instance, in June 2022, FedEx Corporation (U.S.) invested in FourKites, Inc. (U.S.), a supply chain visibility startup. This strategic collaboration allows FedEx to leverage its machine learning and AI capabilities with data from FedEx, enhancing its operational efficiency and visibility.

Based on deployment mode, the AI in supply chain market is segmented into cloud-based deployments and on-premise deployments. In 2024, the cloud-based deployments segment is expected to account for the larger share of 75.6% of the AI in supply chain market. The large market share of this segment is attributed to the increasing avenues for cloud-based deployments, the superior flexibility and affordability offered by cloud-based deployments, and the increasing adoption of cloud-based solutions by small & medium-sized enterprises.

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Based on application, the AI in supply chain market is segmented into demand forecasting, supply chain planning, warehouse management, fleet management, risk management, inventory management, predictive maintenance, real-time supply chain visibility, and other applications. In 2024, the demand forecasting segment is expected to account for the largest share of 25.2% of the AI in supply chain market. The large market share of this segment is attributed to the rising initiatives to integrate AI capabilities in supply chain solutions, dynamic changes in customer behaviors and expectations, and the rising need to achieve accuracy and resilience in the supply chain. For instance, in March 2023, Zionex, Inc. (South Korea), a prominent provider of advanced supply chain and integrated business planning platforms, launched PlanNEL Beta. This AI-powered SaaS platform is designed for demand forecasting and inventory optimization.

 

Based on end-use industry, the AI in supply chain market is segmented into manufacturing, food and beverage, healthcare & pharmaceuticals, automotive, retail, building & construction, medical devices & consumables, aerospace & defense, and other end-use industries. In 2024, the manufacturing segment is expected to account for the largest share of 23.1% of the AI in supply chain market. The large market share of this segment is attributed to the increasing number of manufacturing companies, favorable initiatives to integrate artificial capabilities in the supply chain, and the increasing focus on achieving accuracy and resilience in the supply chain among manufacturers.

Based on geography, the AI in supply chain market is segmented into North America, Europe, Asia-Pacific, Latin America, and the Middle East & Africa. In 2024, Asia-Pacific is expected to account for the largest share of 36.9% of the AI in supply chain market. The large market share of this region is attributed to the rapid pace of digitalization and modernization across industries, the advent of Industry 4.0, and the growing adoption of advanced technologies across various businesses.

Key Players:

Some of the key players operating in the AI in supply chain market are IBM Corporation (U.S.), SAP SE (Germany), Microsoft Corporation (U.S.), Google LLC (U.S.), Amazon Web Services, Inc. (U.S.), Intel Corporation (U.S.), NVIDIA Corporation (U.S.), Oracle Corporation (U.S.), C3.ai, Inc. (U.S.), Samsung SDS CO., Ltd. (South Korea), Coupa Software Inc. (U.S.), Micron Technology, Inc. (U.S.), Advanced Micro Devices, Inc. (U.S.), , FedEx Corporation (U.S.), and Deutsche Post DHL Group (Germany).

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Scope of the report:

AI in Supply Chain Market Assessment, by Offering

  • Hardware
    • Processors
    • Networking
    • Storage
  • Software
  • Services
    • Deployment & Integration Services
    • Support & Maintenance Services
    • Consulting Services
    • Connectivity Services

AI in Supply Chain Market Assessment, by Technology

  • Machine Learning
  • Computer Vision
  • Natural Language Processing
  • Context-aware Computing
  • Robotic Process Automation

AI in Supply Chain Market Assessment, by Deployment Mode

  • Cloud-based Deployments
  • On-premise Deployments

AI in Supply Chain Market Assessment, by Application

  • Demand Forecasting 
  • Supply Chain Planning
  • Warehouse Management
  • Fleet Management
  • Inventory Management
  • Real-time Supply Chain Visibility
  • Other Applications

AI in Supply Chain Market Assessment, by End-Use Industry

  • Manufacturing
  • Food and Beverage
  • Healthcare & Pharmaceuticals
  • Automotive
  • Retail
  • Building & Construction
  • Medical Devices & Consumables
  • Aerospace & Defense
  • Other End-use Industries

AI in Supply Chain Market Assessment, by Geography

  • North America
    • U.S.
    • Canada
  • Europe
    • Germany
    • U.K.
    • France
    • Italy
    • Spain
    • Sweden
    • Rest of Europe
  • Asia-Pacific
    • China
    • Japan
    • India
    • South Korea
    • Singapore
    • Rest of Asia-Pacific
  • Latin America
    • Brazil
    • Mexico
    • Rest of Latin America
  • Middle East & Africa
    • UAE
    • Israel
    • Rest of the Middle East & Africa

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