Insights on the Artificial Intelligence in Supply Chain Management Global Market to 2026 - Integration of AI with Internet of Things Presents ...

Source: Research and Markets

March 22, 2021 05:38 ET

Insights on the Artificial Intelligence in Supply Chain Management Global
Market to 2026 - Integration of AI with Internet of Things Presents
Opportunities
Dublin, March 22, 2021 (GLOBE NEWSWIRE) -- 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:

      AI in SCM solutions as a whole will reach $15.5B globally by 2026
      The Asia Pac region is the largest and fastest-growing for AI in SCM
      Cloud-based AI-as-a-Service for SCM will exceed $2.3B globally by 2026
      AI SCM in edge computing for IoT enabled solutions will reach $4.8B by 2026
      Artificial Intelligence of Things is emerging as a major enabler of SCM optimization
      Material movement and tracking is the largest sub-segment within AI SCM in the manufacturing
      Leading vendors covered include SAP, Oracle, JDA, Epicor Software, Infor Global, and others
      AI-enabled supply chains are over 65% more effective with reduced risk and lower overall costs

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 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

3.0 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. Legacy Integration

4.0 Supply Chain Ecosystem Company Analysis
4.1 Vendor Market Share
4.2 Top Vendor Recent Developments
4.3 3M
4.4 Adidas
4.5 Amazon
4.6 Arvato SCM Solutions
4.7 BASF
4.8 Basware
4.9 BMW
4.10 C. H.Robinson
4.11 Cainiao Network (Alibaba)
4.12 Cisco Systems
4.13 ClearMetal
4.14 Coca-Cola Co.
4.15 Colgate-Palmolive
4.16 Coupa Software
4.17 Descartes Systems Group
4.18 Diageo
4.19 E2open

4.20 Epicor Software Corporation
4.21 FedEx
4.22 Fraight AI
4.23 H&M
4.24 HighJump
4.25 Home Depot
4.26 HP Inc.
4.27 IBM
4.28 Inditex
4.29 Infor Global Solutions
4.30 Intel
4.31 JDA
4.32 Johnson & Johnson
4.33 Kimberly-Clark
4.34 L'Oreal
4.35 LLamasoft Inc.
4.36 Logility
4.37 Manhattan Associates
4.38 Micron Technology
4.39 Microsoft
4.40 Nestle
4.41 Nike
4.42 Novo Nordisk
4.43 NVidia
4.44 Oracle
4.45 PepsiCo
4.46 Presenso
4.47 Relex Solution
4.48 Sage
4.49 Samsung Electronics
4.50 SAP
4.51 Schneider Electric
4.52 SCM Solutions Corp.
4.53 Splice Machine
4.54 Starbucks
4.55 Teknowlogi
4.56 Unilever
4.57 Walmart
4.58 Xilinx

5.0 AI in SCM Market Case Studies
5.1 IBM Case Study with the Master Lock Company
5.2 BASF: Supporting smarter supply chain operations with cognitive cloud technology
5.3 Amazon Customer Retention Case Study
5.4 BMW Employs AI for Logistics Processes
5.5 Intelligent Revenue and Supply Chain Management
5.6 AI-Powered Customer Experience
5.7 Rolls Royce uses AI to safely transport its Cargo
5.8 Robots deliver medicine, groceries and packages with AI
5.9 Lineage Logistics Company Case Study

6.0 AI in SCM Market Analysis and Forecasts 2021 - 2026
6.1 AI in SCM Market 2021 - 2026
6.2 AI in SCM by Solution 2021 - 2026
6.2.1 Platforms
6.2.2 Software
6.2.3 AI as a Service
6.3 AI in SCM by Solution Components 2021 - 2026
6.3.1 Hardware
6.3.1.1 Non-IoT Device
6.3.1.2 IoT Embedded Device
6.3.1.2.1 Security Devices
6.3.1.2.2 Surveillance Robots and Drone
6.3.1.2.3 Networking Devices
6.3.1.2.4 Smart Appliances
6.3.1.2.5 Healthcare Device

6.3.1.2.6 Smart Grid Devices
6.3.1.2.7 In-Vehicle Devices
6.3.1.2.8 Energy Management Device
6.3.1.3 Components
6.3.1.3.1 Wearable and Embedded Components
6.3.1.3.1.1 Real-Time Location System (RTLS)
6.3.1.3.1.2 Barcode
6.3.1.3.1.3 Barcode Scanner
6.3.1.3.1.4 Barcode Stickers
6.3.1.3.1.5 RFID
6.3.1.3.1.6 RFID Tags
6.3.1.3.1.7 Sensor
6.3.1.3.2 Processors
6.3.2 Software
6.3.3 Services
6.3.3.1 Professional Services
6.4 AI in SCM by Management Function 2021 - 2026
6.4.1 Automation
6.4.2 Planning and Logistics
6.4.3 Inventory Management
6.4.4 Fleet Management
6.4.5 Virtual Assistance
6.4.6 Freight Brokerage
6.4.7 Risk Management and Dispute Resolution
6.5 AI in SCM by Technology 2021 - 2026
6.5.1 Cognitive Computing
6.5.2 Computer Vision
6.5.3 Context-aware Computing
6.5.4 Natural Language Processing
6.5.5 Predictive Analytics
6.5.6 Machine Learning
6.5.6.1 Reinforcement Learning
6.5.6.2 Supervised Learning
6.5.6.3 Unsupervised Learning
6.5.6.4 Deep Learning
6.6 AI in SCM by Industry Vertical 2021 - 2026
6.6.1 Aerospace and Government
6.6.2 Automotive and Transportation
6.6.3 Retail and Consumer Electronics
6.6.4 Consumer Goods
6.6.5 Healthcare
6.6.6 Manufacturing
6.6.7 Building and Construction
6.6.8 Others
6.7 AI in SCM by Deployment 2021 - 2026
6.7.1 Cloud Deployment
6.8 AI in SCM by AI System 2021 - 2026
6.9 AI in SCM by AI Type 2021 - 2026
6.10 AI in SCM by Connectivity
6.10.1 Non-Telecom Connectivity
6.10.2 Telecom Connectivity
6.10.3 Connectivity Standard
6.10.4 Enterprise
6.11 AI in SCM Market by IoT Edge Network 2021 - 2026
6.12 AI in SCM Analytics Market 2021 - 2026
6.13 AI in SCM Market by Intent Based Networking 2021 - 2026
6.14 AI in SCM Market by Virtualization 2021 - 2026
6.15 AI in SCM Market by 5G Network 2021 - 2026
6.16 AI in SCM Market by Blockchain Network 2021 - 2026
6.17 AI in SCM by Region 2021 - 2026
6.17.1 North America
6.17.2 Asia Pacific
6.17.3 Europe
6.17.4 Middle East and Africa
6.17.5 Latin America
6.18 AI in SCM by Country

6.18.1 Top Ten Country Market Share
6.18.2 USA
6.18.3 China
6.18.4 Canada
6.18.5 Mexico
6.18.6 Japan
6.18.7 UK
6.18.8 Germany
6.18.9 South Korea
6.18.10 France
6.18.11 Russia

7.0 Summary and Recommendations

For more information about this report visit https://www.researchandmarkets.com/r/uhqabi