DUBLIN, March 19, 2021 /PRNewswire/ -- The "Artificial Intelligence in Supply Chain Management Market by Technology, Processes, Solutions, Management Function (Automation, Planning and Logistics, Inventory, Risk), Deployment Model, Business Type and Industry Verticals 2021 - 2026" report has been added to ResearchAndMarkets.com's offering.
This report provides detailed analysis and forecasts for AI in SCM by solution (Platforms, Software, and AI as a Service), solution components (Hardware, Software, Services), management function (Automation, Planning and Logistics, Inventory Management, Fleet Management, Freight Brokerage, Risk Management, and Dispute Resolution), AI technologies (Cognitive Computing, Computer Vision, Context-aware Computing, Natural Language Processing, and Machine Learning), and industry verticals (Aerospace, Automotive, Consumer Goods, Healthcare, Manufacturing, and others).
This is the broadest and detailed report of its type, providing analysis across a wide range of go-to-operational process considerations, such as the need for identity management and real-time location tracking, and market deployment considerations, such as AI type, technologies, platforms, connectivity, IoT integration, and deployment model including AI-as-a-Service (AIaaS). Each aspect evaluated includes forecasts from 2021 to 2026 such as AIaaS by revenue in China. It provides an analysis of AI in SCM globally, regionally, and by country including the top ten countries per region by market share.
The report provides an analysis of leading companies and solutions that are leveraging AI in their supply chains and those they manage on behalf of others, with an evaluation of key strengths and weaknesses of these solutions. It assesses AI in SCM by industry vertical and application such as material movement tracking and drug supply management in manufacturing and healthcare respectively. The report also provides a view into the future of AI in SCM including analysis of performance improvements such as optimization of revenues, supply chain satisfaction, and cost reduction.
Select Report Findings:
Modern supply chains represent complex systems of organizations, people, activities, information, and resources involved in moving a product or service from supplier to customer. Supply Chain Management (SCM) solutions are typically manifest in software architecture and systems that facilitate the flow of information among different functions within and between enterprise organizations.
Leading SCM solutions catalyze information sharing across organizational units and geographical locations, enabling decision-makers to have an enterprise-wide view of the information needed in a timely, reliable and consistent fashion. Various forms of Artificial Intelligence (AI) are being integrated into SCM solutions to improve everything from process automation to overall decision-making. This includes greater data visibility (static and real-time data) as well as related management information system effectiveness.
In addition to fully automated decision-making, AI systems are also leveraging various forms of cognitive computing to optimize the combined efforts of artificial and human intelligence. For example, AI in SCM is enabling improved supply chain automation through the use of virtual assistants, which are used both internally (within a given enterprise) as well as between supply chain members (e.g. customer-supplier chains). It is anticipated that virtual assistants in SCM will leverage an industry-specific knowledge database as well as company, department, and production-specific learning.
AI-enabled improvements in supply chain member satisfaction causes a positive feedback loop, leading to better overall SCM performance. One of the primary goals is to leverage AI to make supply chain improvements from production to consumption within product-related industries as well as create opportunities for supporting "servitization" of products in a cloud-based "as a service" model. AI will identify opportunities for supply chain members to have greater ownership of "outcomes as a service" and control of overall product/service experience and profitability.
With Internet of Things (IoT) technologies and solutions taking an ever-increasing role in SCM, the inclusion of AI algorithms and software-driven processes with IoT represents a very important opportunity to leverage the Artificial Intelligence of Things (AIoT) in supply chains. More specifically, AIoT solutions leverage the connectivity and communications power of IoT, along with the machine learning and decision-making capabilities of AI, as a means of optimizing SCM by way of data-driven managed services.
Key Topics Covered:
1.0 Executive Summary
2.0 Introduction2.1 Supply Chain Management2.1.1 Challenges2.1.2 Opportunities2.2 AI in SCM2.2.1 Key AI Technologies for SCM2.2.2 AI and Technology Integration
3.0 AI in SCM Challenges and Opportunities3.1 Market Dynamics3.1.1 Companies with Complex Supply Chains3.1.2 Logistics Management Companies3.1.3 SCM Software Solution Companies3.2 Technology and Solution Opportunities3.2.1 Leverage Artificial Intelligence (AI)3.2.1.1 Integrate AI with Existing Processes3.2.1.2 Integrate AI with Existing Systems3.2.2 Integrate AI with Internet of Things (IoT)3.2.2.1 Leverage AIoT Platforms, Software, and Services3.2.2.2 Leverage Data as a Service Providers3.3 Implementation Challenges3.3.1 Management Friction3.3.2 Legacy Processes and Procedures3.3.3 Outsource AI SCM Solution vs. Legacy Integration
4.0 Supply Chain Ecosystem Company Analysis4.1 Vendor Market Share4.2 Top Vendor Recent Developments4.3 3M4.4 Adidas4.5 Amazon4.6 Arvato SCM Solutions4.7 BASF4.8 Basware4.9 BMW4.10 C. H.Robinson4.11 Cainiao Network (Alibaba)4.12 Cisco Systems4.13 ClearMetal4.14 Coca-Cola Co.4.15 Colgate-Palmolive4.16 Coupa Software4.17 Descartes Systems Group4.18 Diageo4.19 E2open4.20 Epicor Software Corporation4.21 FedEx4.22 Fraight AI4.23 H&M4.24 HighJump4.25 Home Depot4.26 HP Inc.4.27 IBM4.28 Inditex4.29 Infor Global Solutions4.30 Intel4.31 JDA4.32 Johnson & Johnson4.33 Kimberly-Clark4.34 L'Oreal4.35 LLamasoft Inc.4.36 Logility4.37 Manhattan Associates4.38 Micron Technology4.39 Microsoft4.40 Nestle4.41 Nike4.42 Novo Nordisk4.43 NVidia4.44 Oracle4.45 PepsiCo4.46 Presenso4.47 Relex Solution4.48 Sage4.49 Samsung Electronics4.50 SAP4.51 Schneider Electric4.52 SCM Solutions Corp.4.53 Splice Machine4.54 Starbucks4.55 Teknowlogi4.56 Unilever4.57 Walmart4.58 Xilinx
5.0 AI in SCM Market Case Studies5.1 IBM Case Study with the Master Lock Company5.2 BASF: Supporting smarter supply chain operations with cognitive cloud technology5.3 Amazon Customer Retention Case Study5.4 BMW Employs AI for Logistics Processes5.5 Intelligent Revenue and Supply Chain Management5.6 AI-Powered Customer Experience5.7 Rolls Royce uses AI to safely transport its Cargo5.8 Robots deliver medicine, groceries and packages with AI5.9 Lineage Logistics Company Case Study
6.0 AI in SCM Market Analysis and Forecasts 2021 - 20266.1 AI in SCM Market 2021 - 20266.2 AI in SCM by Solution 2021 - 20266.2.1 Platforms6.2.2 Software6.2.3 AI as a Service6.3 AI in SCM by Solution Components 2021 - 20266.3.1 Hardware6.3.1.1 Non-IoT Device6.3.1.2 IoT Embedded Device6.3.1.2.1 Security Devices6.3.1.2.2 Surveillance Robots and Drone6.3.1.2.3 Networking Devices6.3.1.2.4 Smart Appliances6.3.1.2.5 Healthcare Device6.3.1.2.6 Smart Grid Devices6.3.1.2.7 In-Vehicle Devices6.3.1.2.8 Energy Management Device6.3.1.3 Components6.3.1.3.1 Wearable and Embedded Components6.3.1.3.1.1 Real-Time Location System (RTLS)6.3.1.3.1.2 Barcode6.3.1.3.1.3 Barcode Scanner6.3.1.3.1.4 Barcode Stickers6.3.1.3.1.5 RFID6.3.1.3.1.6 RFID Tags6.3.1.3.1.7 Sensor6.3.1.3.2 Processors6.3.2 Software6.3.3 Services6.3.3.1 Professional Services6.4 AI in SCM by Management Function 2021 - 20266.4.1 Automation6.4.2 Planning and Logistics6.4.3 Inventory Management6.4.4 Fleet Management6.4.5 Virtual Assistance6.4.6 Freight Brokerage6.4.7 Risk Management and Dispute Resolution6.5 AI in SCM by Technology 2021 - 20266.5.1 Cognitive Computing6.5.2 Computer Vision6.5.3 Context-aware Computing6.5.4 Natural Language Processing6.5.5 Predictive Analytics6.5.6 Machine Learning6.5.6.1 Reinforcement Learning6.5.6.2 Supervised Learning6.5.6.3 Unsupervised Learning6.5.6.4 Deep Learning6.6 AI in SCM by Industry Vertical 2021 - 20266.6.1 Aerospace and Government6.6.2 Automotive and Transportation6.6.3 Retail and Consumer Electronics6.6.4 Consumer Goods6.6.5 Healthcare6.6.6 Manufacturing6.6.7 Building and Construction6.6.8 Others6.7 AI in SCM by Deployment 2021 - 20266.7.1 Cloud Deployment6.8 AI in SCM by AI System 2021 - 20266.9 AI in SCM by AI Type 2021 - 20266.10 AI in SCM by Connectivity6.10.1 Non-Telecom Connectivity6.10.2 Telecom Connectivity6.10.3 Connectivity Standard6.10.4 Enterprise6.11 AI in SCM Market by IoT Edge Network 2021 - 20266.12 AI in SCM Analytics Market 2021 - 20266.13 AI in SCM Market by Intent Based Networking 2021 - 20266.14 AI in SCM Market by Virtualization 2021 - 20266.15 AI in SCM Market by 5G Network 2021 - 20266.16 AI in SCM Market by Blockchain Network 2021 - 20266.17 AI in SCM by Region 2021 - 20266.17.1 North America6.17.2 Asia Pacific6.17.3 Europe6.17.4 Middle East and Africa6.17.5 Latin America6.18 AI in SCM by Country6.18.1 Top Ten Country Market Share6.18.2 USA6.18.3 China6.18.4 Canada6.18.5 Mexico6.18.6 Japan6.18.7 UK6.18.8 Germany6.18.9 South Korea6.18.10 France6.18.11 Russia
7.0 Summary and Recommendations
For more information about this report visit https://www.researchandmarkets.com/r/bxs2vn
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