Market Overview

Outlook on the Worldwide AI in Supply Chain Market to 2027 - Evolving Supply Chain Automation Presents Opportunities

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Dublin, April 07, 2020 (GLOBE NEWSWIRE) -- The "Artificial Intelligence in Supply Chain Market by Component (Platforms, Solutions) Technology (Machine Learning, Computer Vision, Natural Language Processing), Application (Warehouse, Fleet, Inventory Management), and by End User - Global Forecast to 2027" report has been added to ResearchAndMarkets.com's offering.

This report carries out an impact analysis of the key industry drivers, restraints, challenges, and opportunities. Adoption of artificial intelligence in the supply chain allows industries to track their operations, enhance supply chain management productivity, augment business strategies, and engage with customers in the digital world.

The growth of artificial intelligence in supply chain market is driven by several factors such as raising awareness of artificial intelligence and big data & analytics and widening implementation of computer vision in both autonomous & semi-autonomous applications. Moreover, the factors such as consistent technological advancements in the supply chain industry, rising demand for AI-based business automation solutions, and evolving supply chain automation are also contributing to the market growth.

The overall AI in supply chain market is segmented by component (hardware, software, and services), by technology (machine learning, computer vision, natural language processing, cognitive computing, and context-aware computing), by application (supply chain planning, warehouse management, fleet management, virtual assistant, risk management, inventory management, and planning & logistics), and by end-user (manufacturing, food and beverages, healthcare, automotive, aerospace, retail, and consumer-packaged goods), and geography.

Based on technology, the machine learning segment accounted for the largest share of the overall artificial intelligence in supply chain market in 2019, driven by the growing demand for AI-based intelligent solutions; increasing government initiatives; and the ability of AI solutions to efficiently handle and analyze big data and quickly scan, parse, and react to anomalies. However, the computer vision technology segment is slated to grow at the fastest CAGR during the forecast period, due to growing implementation of computer vision across several end-use industries for monitoring operations, spotting suspicious behavior, and preventing thefts.

Based on application, the supply chain planning segment accounted for the largest share of the overall AI in supply chain market in 2019, and is also expected to witness high growth during the forecast period, mainly due to the growing demand for enhancing factory scheduling & production planning and the evolving agility and optimization of supply chain decision-making.

An in-depth analysis of the geographic scenario of the market provides detailed qualitative and quantitative insights about the five regions including North America, Europe, Asia Pacific, Latin America, and the Middle East and Africa. In 2019, North America commanded the largest share of the global artificial intelligence in supply chain market, followed by Europe and Asia Pacific. The large share of this region is mainly attributed to its open-minded approach towards smart technologies & high technology adoption rate and the presence of developed economies focusing on enhancing the existing solutions in the supply chain space. However, the factors such as growing proliferation of the Internet of Things (IoT), growing adoption of AI-based solutions and services among supply chain operations, and government initiatives to increase digitalization are helping Asia Pacific to register the fastest growth in the overall artificial intelligence in supply chain market.

Some of the key players operating in global artificial intelligence in supply chain market are Intel Corporation (U.S.), Amazon.com, Inc. (U.S.), Google LLC (U.S.), Microsoft Corporation (U.S.), Nvidia Corporation (U.S.), Oracle Corporation (U.S.), IBM Corporation (U.S.), Samsung (South Korea), LLamasoft, Inc. (U.S.), SAP SE (Germany), General Electric (U.S.), Deutsche Post DHL Group (Germany), Xilinx, Inc. (U.S.), Micron Technology, Inc. (U.S.), FedEx Corporation (U.S.), ClearMetal, Inc. (U.S.), Dassault Systmes (France), and JDA Software Group, Inc. (U.S.) along with several local and regional players.

Key Topics Covered:

1. Introduction

2. Research Methodology

3. Executive Summary
3.1. Overview
3.2. Market Analysis, by Component
3.3. Market Analysis, by Technology
3.4. Market Analysis, by Application
3.5. Market Analysis, by End User
3.6. Market Analysis, by Geography
3.7. Competitive Analysis

4. Market Insights
4.1. Introduction
4.2. Market Dynamics
4.2.1. Drivers
4.2.1.1. Rising Awareness of Artificial Intelligence and Big Data & Analytics
4.2.1.2. Widening Implementation of Computer Vision in both Autonomous & Semi-Autonomous Applications
4.2.2. Restraints
4.2.2.1. High Procurement and Operating Cost
4.2.2.2. Lack of Infrastructure
4.2.3. Opportunities
4.2.3.1. Growing Demand for AI -Based Business Automation Solutions
4.2.3.2. Evolving Supply Chain Automation
4.2.4. Challenges
4.2.4.1. Data Integration from Multiple Resources
4.2.4.2. Concerns Over Data Privacy
4.2.5. Trends
4.2.5.1. Rising Adoption of 5g Technology
4.2.5.2. Rising Demand for Cloud-Based Supply Chain Solutions

5. Artificial Intelligence in Supply Chain Market, by Component
5.1. Introduction
5.2. Software
5.2.1. AI Platforms
5.2.2. AI Solutions
5.3. Services
5.3.1. Deployment & Integration
5.3.2. Support & Maintenance
5.4. Hardware
5.4.1. Networking
5.4.2. Memory
5.4.3. Processors

6. Artificial Intelligence in Supply Chain Market, by Technology
6.1. Introduction
6.2. Machine Learning
6.3. Natural Language Processing (NLP)
6.4. Computer Vision
6.5. Context-Aware Computing

7. Artificial Intelligence in Supply Chain Market, by Application
7.1. Introduction
7.2. Supply Chain Planning
7.3. Virtual Assistant
7.4. Risk Management
7.5. Inventory Management
7.6. Warehouse Management
7.7. Fleet Management
7.8. Planning & Logistics

8. Artificial Intelligence in Supply Chain Market, by End User
8.1. Introduction
8.2. Retail Sector
8.3. Manufacturing Sector
8.4. Automotive Sector
8.5. Aerospace Sector
8.6. Food & Beverage Sector
8.7. Consumer Packaged Goods Sector
8.8. Healthcare Sector

9. Global Artificial Intelligence in Supply Chain Market, by Geography
9.1. Introduction
9.2. North America
9.2.1. U.S.
9.2.2. Canada
9.3. Europe
9.3.1. Germany
9.3.2. U.K.
9.3.3. France
9.3.4. Spain
9.3.5. Italy
9.3.6. Rest of Europe
9.4. Asia-Pacific
9.4.1. China
9.4.2. Japan
9.4.3. India
9.4.4. Rest of Asia-Pacific
9.5. Latin America
9.6. Middle East & Africa

10. Competitive Landscape
10.1. Key Growth Strategies
10.2. Competitive Developments
10.2.1. New Product Launches and Upgradations
10.2.2. Mergers and Acquisitions
10.2.3. Partnerships, Agreements, & Collaborations
10.2.4. Expansions
10.3. Market Share Analysis
10.4. Competitive Benchmarking

11. Company Profiles (Business Overview, Financial Overview, Product Portfolio, Strategic Developments)
11.1. Intel Corporation
11.2. Amazon.Com, Inc.
11.3. Google LLC
11.4. Microsoft Corporation
11.5. Nvidia Corporation
11.6. Oracle Corporation
11.7. IBM Corporation
11.8. Samsung
11.9. Llamasoft, Inc.
11.10. Sap SE
11.11. General Electric Company
11.12. Deutsche Post DHL Group
11.13. Xilinx, Inc.
11.14. Micron Technology, Inc.
11.15. FedEx Corporation
11.16. Clearmetal, Inc.
11.17. Dassault Systmes SE
11.18. JDA Software Group, Inc.

12. Appendix

For more information about this report visit https://www.researchandmarkets.com/r/d01wp7

Research and Markets also offers Custom Research services providing focused, comprehensive and tailored research.

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