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市場調査レポート
商品コード
1486916
サプライチェーン向けAIの市場規模、シェア、予測、動向分析:提供別、技術別、展開モード別、アプリケーション別、最終用途産業別、地域別 - 2031年までの世界予測AI in Supply Chain Market Size, Share, Forecast, & Trends Analysis by Offering, Technology, Deployment Mode, Application, End-use Industry & Geography - Global Forecasts to 2031 |
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サプライチェーン向けAIの市場規模、シェア、予測、動向分析:提供別、技術別、展開モード別、アプリケーション別、最終用途産業別、地域別 - 2031年までの世界予測 |
出版日: 2024年05月30日
発行: Meticulous Research
ページ情報: 英文 282 Pages
納期: 即納可能
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サプライチェーン向けAI市場は、2024年から2031年までのCAGRが40.4%で、2031年までに585億5,000万米ドルに達すると予測されています。この市場の成長は、サプライチェーン業務への人工知能の導入が進んでいることと、サプライチェーンプロセスにおける可視性と透明性の向上に対するニーズが高まっていることが背景にあります。しかし、AIベースのサプライチェーンソリューションの調達・運用コストが高く、サポートするインフラが不足していることが、この市場の成長を抑制しています。
さらに、AIベースのビジネス自動化ソリューションに対する需要の高まりは、この市場で事業を展開するプレーヤーに成長機会をもたらすと期待されています。しかし、複数のソースからのデータを統合する際のパフォーマンス上の問題や、データのセキュリティとプライバシーに関する懸念は、市場の成長に影響を与える主要な課題です。さらに、クラウドベースのサプライチェーンソリューションに対する需要の高まりは、サプライチェーン向けAI市場の顕著な動向です。
(注:上位5社のSWOT分析を掲載)
Figure 31 IBM Corporation: Financial Overview (2023)
Figure 32 SWOT Analysis: IBM Corporation
Figure 33 SAP SE: Financial Overview (2023)
Figure 34 SWOT Analysis: SAP SE
Figure 35 Microsoft Corporation: Financial Overview (2022)
Figure 36 SWOT Analysis: Microsoft Corporation
Figure 37 Alphabet, Inc.: Financial Overview (2023)
Figure 38 SWOT Analysis: Google LLC
Figure 39 Amazon.com, Inc.: Financial Overview (2023)
Figure 40 SWOT Analysis: Amazon Web Services, Inc.
Figure 41 NVIDIA Corporation: Financial Overview (2023)
Figure 42 Oracle Corporation: Financial Overview (2022)
Figure 43 C3.ai, Inc.: Financial Overview (2022)
Figure 44 Intel Corporation: Financial Overview (2023)
Figure 45 Samsung SDS CO., Ltd.: Financial Overview (2023)
Figure 46 Micron Technology, Inc.: Financial Overview (2023)
Figure 47 Advanced Micro Devices, Inc.: Financial Overview (2023)
Figure 48 FedEx Corporation: Financial Overview (2022)
Figure 49 Deutsche Post DHL Group: Financial Overview (2023)
The research report titled 'Global 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', provides in-depth analysis of AI in supply chain market across five major geographies and emphasizes on the current market trends, market sizes, market shares, recent developments, and forecasts till 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 growth of this market is driven by 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 and operating costs of AI-based supply chain solutions and the lack of supporting infrastructure restrain the growth of this market.
Furthermore, the growing demand for AI-based business automation solutions is expected to generate growth opportunities for the players operating in this market. However, performance issues in integrating data from multiple sources and data security & privacy concerns are major challenges impacting market growth. Additionally, the rising demand for cloud-based supply chain solutions is a prominent trend in the AI in supply chain market.
Based on offering, the global 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 the global 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.
However, the software segment is expected to record the highest CAGR during the forecast period. The growth of this segment is driven by the rising focus on product development and the enhancement of supply chain software, and the benefits offered by supply chain software in facilitating supply chain visibility and centralized operations.
Based on technology, the global 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 the global 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.
However, the robotic process automation segment is expected to record the highest CAGR during the forecast period. This segment's growth is driven by the increased adoption of RPA across various industries and the rising demand for automating business processes to meet heightened customer expectations.
Based on deployment mode, the global 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 the global 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.
Moreover, the cloud-based deployments segment is expected to record the highest CAGR during the forecast period. The rapid development of new security measures for cloud-based deployments is expected to drive this segment's growth in the coming years.
Based on application, the global 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 the global 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.
However, the real-time supply chain visibility segment is expected to record the highest CAGR during the forecast period. This segment's growth is driven by the rising integration of AI capabilities into supply chains to obtain real-time data on them.
Based on end-use industry, the global 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 the global 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.
However, the retail segment is expected to record the highest CAGR during the forecast period. This segment's growth is driven by the rising integration of AI capabilities in the retail supply chain to forecast inventory and demand and retailers' growing focus on meeting consumer expectations.
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 the global 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.
Moreover, the Asia-Pacific region is projected to record the highest CAGR during the forecast period. The growth of this market is driven by the proliferation of advanced supply chain solutions, the rising deployment of AI tools across the region, and efforts by major market players to implement AI technology across various sectors.
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).
AI in Supply Chain Market Assessment, by Offering
AI in Supply Chain Market Assessment, by Technology
AI in Supply Chain Market Assessment, by Deployment Mode
AI in Supply Chain Market Assessment, by Application
AI in Supply Chain Market Assessment, by End-Use Industry
AI in Supply Chain Market Assessment, by Geography
(Note: SWOT analysis of the top 5 companies will be provided.)