Dublin, Nov. 15, 2019 (GLOBE NEWSWIRE) — The “Artificial Intelligence (AI) in Supply Chain Management (SCM) Market: AI in SCM by Technology, Solution, Management Function (Automation, Planning and Logistics, Inventory, Fleet, Freight, Risk), and Region 2019-2024” report has been added to ResearchAndMarkets.com’s offering.
Select Findings
- The Global AI in SCM Market by AI-as-a-Service will reach $1.3 Billion by 2024
- AI in SCM for the healthcare industry in North America will reach $183B USD by 2024
- Combination of AI and IoT in supply chains will improve operational flow and efficiency
- AI supported supply chains become 45% more effective at on-time delivery with fewer errors
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 solution to improve everything from process automation to providing greater visibility into static and real-time data as well as related management information systems.
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).
Report Coverage
This research evaluates how AI is revamping the operational process and facilitating cost-effective supply chain solutions. It provides analysis of leading companies and solutions that are leveraging AI in their supply chains and those they manage on behalf of others, with evaluation of key strengths and weaknesses of these solutions. The report also provides a view into the future of AI in supply chain management.
The 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).
Key Topics Covered
1. Executive Summary
2. Introduction
2.1 Supply Chain Management
2.1.1 Challenges
2.1.2 Opportunities
2.2 AI in SCM
2.2.1 Key AI Technologies for SCM
2.2.2 AI and Technology Integration
3. AI in SCM Challenges and Opportunities
3.1 Market Dynamics
3.1.1 Companies with Complex Supply Chains
3.1.2 Logistics Management Companies
3.1.3 SCM Software Solution Companies
3.2 Technology and Solution Opportunities
3.2.1 Leverage Artificial Intelligence (AI)
3.2.1.1 Integrate AI with Existing Processes
3.2.1.2 Integrate AI with Existing Systems
3.2.2 Integrate AI with Internet of Things (IoT)
3.2.2.1 Leverage AIoT Platforms, Software, and Services
3.2.2.2 Leverage Data as a Service Providers
3.3 Implementation Challenges
3.3.1 Management Friction
3.3.2 Legacy Processes and Procedures
3.3.3 Outsource AI SCM Solution vs. Integrate with Existing
4. Supply Chain Ecosystem Company Analysis
4.1 Vendor Market Share
4.2 3M
4.3 Adidas
4.4 Amazon
4.5 Arvato SCM Solutions
4.6 BASF
4.7 Basware
4.8 BMW
4.9 C. H. Robinson
4.10 Cainiao Network (Alibaba)
4.11 Cisco Systems
4.12 ClearMetal
4.13 Coca-Cola Co.
4.14 Colgate-Palmolive
4.15 Coupa Software
4.16 Descartes Systems Group
4.17 Diageo
4.18 E2open
4.19 Epicor Software Corporation
4.20 FedEx
4.21 Fraight AI
4.22 H&M
4.23 HighJump
4.24 Home Depot
4.25 HP Inc.
4.26 IBM
4.27 Inditex
4.28 Infor Global Solutions
4.29 Intel
4.30 JDA
4.31 Johnson & Johnson
4.32 Kimberly-Clark
4.33 L’Oreal
4.34 LLamasoft Inc.
4.35 Logility
4.36 Manhattan Associates
4.37 Micron Technology
4.38 Microsoft
4.39 Nestle
4.40 Nike
4.41 Novo Nordisk
4.42 NVidia
4.43 Oracle
4.44 PepsiCo
4.45 Presenso
4.46 Relex Solution
4.47 Sage
4.48 Samsung Electronics
4.49 SAP
4.50 Schneider Electric
4.51 SCM Solutions Corp.
4.52 Splice Machine
4.53 Starbucks
4.54 Teknowlogi
4.55 Unilever
4.56 Walmart
4.57 Xilinx
5. AI in SCM Market Analysis and Forecasts 2019 – 2024
5.1 AI in SCM Market 2019 – 2024
5.2 AI in SCM by Solution 2019 – 2024
5.2.1 Platforms
5.2.2 Software
5.2.3 AI as a Service
5.3 AI in SCM by Solution Components 2019 – 2024
5.3.1 Hardware
5.3.1.1 Non-IoT Device
5.3.1.2 IoT Embedded Device
5.3.1.2.1 Security Devices
5.3.1.2.2 Surveillance Robots and Drone
5.3.1.2.3 Networking Devices
5.3.1.2.4 Smart Appliances
5.3.1.2.5 Medical and Healthcare Device
5.3.1.2.6 Smart Grid Devices
5.3.1.2.7 In-Vehicle Devices
5.3.1.2.8 Energy Management Device
5.3.1.3 Components
5.3.1.3.1 Wearable and Embedded Components
5.3.1.3.1.1 Real Time Location System (RTLS)
5.3.1.3.1.2 Barcode
5.3.1.3.1.3 Barcode Scanner
5.3.1.3.1.4 Barcode Stickers
5.3.1.3.1.5 RFID
5.3.1.3.1.6 RFID Tags
5.3.1.3.1.7 Sensor
5.3.1.3.2 Processors
5.3.2 Software
5.3.3 Services
5.3.3.1 Professional Services
5.4 AI in SCM by Management Function 2019 – 2024
5.4.1 Automation
5.4.2 Planning and Logistics
5.4.3 Inventory Management
5.4.4 Fleet Management
5.4.5 Virtual Assistance
5.4.6 Freight Brokerage
5.4.7 Risk Management and Dispute Resolution
5.5 AI in SCM by Technology 2019 – 2024
5.5.1 Cognitive Computing
5.5.2 Computer Vision
5.5.3 Context-aware Computing
5.5.4 Natural Language Processing
5.5.5 Predictive Analytics
5.5.6 Machine Learning
5.5.6.1 Reinforcement Learning
5.5.6.2 Supervised Learning
5.5.6.3 Unsupervised Learning
5.5.6.4 Deep Learning
5.6 AI in SCM by Industry Vertical 2019 – 2024
5.6.1 Aerospace and Government
5.6.2 Automotive and Transportation
5.6.3 Retail and Consumer Electronics
5.6.4 Consumer Goods
5.6.5 Healthcare and Medical
5.6.6 Manufacturing
5.6.7 Building and Construction
5.6.8 Others
5.7 AI in SCM by Deployment 2019 – 2024
5.7.1 Cloud Deployment
5.8 AI in SCM by AI System 2019 – 2024
5.9 AI in SCM by AI Type
5.10 AI in SCM by Connectivity 2019 – 2024
5.10.1 Non-Telecom Connectivity
5.10.2 Telecom Connectivity
5.10.3 Connectivity Standard
5.10.4 Enterprise
5.11 AI in SCM Market by IoT Edge Network 2019 – 2024
5.12 AI in SCM Analytics Market 2019 – 2024
5.13 AI in SCM Market by Intent Based Networking 2019 – 2024
5.14 AI in SCM Market by Virtualization 2019 – 2024
5.15 AI in SCM Market by 5G Network 2019 – 2024
5.16 AI in SCM Market by Blockchain Network 2019 – 2024
5.17 AI in SCM by Region 2019 – 2024
5.17.1 North America
5.17.2 Asia Pacific
5.17.3 Europe
5.17.4 Middle East and Africa
5.17.5 Latin America
5.18 AI in SCM by Country 2019 – 2024
5.18.1 Top Ten Country Market Share
5.18.2 USA
5.18.3 China
5.18.4 Canada
5.18.5 Mexico
5.18.6 Japan
5.18.7 UK
5.18.8 Germany
5.18.9 South Korea
5.18.10 France
5.18.11 Russia
6. Summary and Recommendations
6.1 Artificial Intelligence Providers
6.2 Automation System Providers
6.3 Communication Service Providers
6.4 Computing Companies
6.5 Data Analytics Providers
6.6 Enterprise and Government
6.7 Immersive Technology (AR, VR, and MR) Providers
6.8 IoT Suppliers and Service Providers
6.9 Logistics Management Companies
6.10 Semiconductor Companies
For more information about this report visit https://www.researchandmarkets.com/r/psiwbz
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