Global Artificial Intelligence in Supply Chain Management Market (2021 to 2026) – by Technology, Processes, Solutions, Management Function, Deployment Model, Business Type and Industry Verticals – ResearchAndMarkets.com

DUBLIN–(BUSINESS WIRE)–The “Artificial Intelligence in Supply Chain Management Market by Technology, Processes, Solutions, Management Function

DUBLIN–(BUSINESS WIRE)–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

Companies Mentioned

  • 3M
  • Adidas
  • Amazon
  • Arvato SCM Solutions
  • BASF
  • Basware
  • BMW
  • C. H.Robinson
  • Cainiao Network (Alibaba)
  • Cisco Systems
  • ClearMetal
  • Coca-Cola Co.
  • Colgate-Palmolive
  • Coupa Software
  • Descartes Systems Group
  • Diageo
  • E2open
  • Epicor Software Corporation
  • FedEx
  • Fraight AI
  • H&M
  • HighJump
  • Home Depot
  • HP Inc.
  • IBM
  • And Many More Companies!

Key Topics Covered:

1.0 Executive Summary

2.0 Introduction

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

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

6.3 AI in SCM by Solution Components 2021 – 2026

6.4 AI in SCM by Management Function 2021 – 2026

6.5 AI in SCM by Technology 2021 – 2026

6.6 AI in SCM by Industry Vertical 2021 – 2026

6.7 AI in SCM by Deployment 2021 – 2026

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

6.11 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

6.18 AI in SCM by Country

7.0 Summary and Recommendations

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