$730 Bn Artificial Intelligence in Supply Chain Market, 2025 Featuring Intel, NVIDIA, Xilinx, Samsung Electronics, Micron Technology, IBM, Microsoft, and Amazon

Press Releases

Feb 18, 2019

DUBLIN, Feb. 18, 2019 /PRNewswire/ — The “Artificial Intelligence in Supply Chain Market by Offering, Technology, Application (Fleet Management, Supply Chain Planning, Warehouse Management, Virtual Assistant, Freight Brokerage), End-User Industry, and Geography – Global Forecast to 2025” report has been added to ResearchAndMarkets.com’s offering

The artificial intelligence in supply chain market is expected to reach USD 10,110.2 million by 2025 from USD 730.6 billion in 2018, at a CAGR of 45.55% during the forecast period.

Growth in this market is mainly driven by factors such as growing big data, demand for greater visibility and transparency into supply chain data and processes, and adoption of AI for improving consumer services and satisfaction. The major restraint for the market is the limited number of the artificial intelligence technology experts.

In this report, the size of the artificial intelligence in supply chain market has been arrived at based on segments such as offerings, technology, application, end-user industry, and region. The artificial intelligence in supply chain market, by offering, is segmented into hardware, software, and services. The software segment is growing at a significant rate. The adoption of AI is increasing rapidly for various applications. Continuous developments have been witnessed in AI and related software development kits. Also, AI software is capable of behaving intelligently. Creating intelligent software involves simulating a number of capabilities, which include reasoning, learning, problem-solving, perception, and knowledge representation.

Depending on the technology, artificial intelligence in supply chain can be segmented into machine learning (ML), natural language processing (NLP), and context-aware computing, and computer vision. The market for computer vision is expected to grow at a higher rate. The growing adoption of computer vision for autonomous or semiautonomous applications in various industries, such as manufacturing and automotive, is propelling the growth of this technology in the artificial intelligence in supply chain market.

Moreover, the market has been segmented, on the basis of end-user industry, into automotive, aerospace, manufacturing, retail, healthcare, consumer-packaged goods, food & beverages, and others. Among all end-user industries, the market for consumer-packaged goods is expected to grow at the highest CAGR during the forecast period. The adoption of AI in consumer goods is increasing as it has ability to collect data, interact with customers, capture images, and more many of these changes are creating a permanent impact on customers’ expectations.

Artificial Intelligence in Supply Chain Market

On the basis of region, the artificial intelligence in supply chain market has been segmented into North America, Europe, Asia Pacific (APAC), and the Rest of the World (RoW). The artificial intelligence in supply chain market in APAC is expected to grow at the highest CAGR during the forecast period. Market growth can be attributed to increasing adoption of deep learning and NLP technologies for automotive, retail, and manufacturing applications in APAC. Moreover, the presence of major players in the artificial intelligence in supply chain ecosystem results in the increasing adoption of artificial intelligence in APAC.

However, the limited number of industry experts for artificial intelligence in supply chain is a major restraint for the market. Key players in this market focus on organic strategies, such as product launches, to expand their business and related offerings.

Some of the players are Intel (US), NVIDIA (US), Xilinx (US), Samsung Electronics (South Korea), Micron Technology (US), IBM (US), Microsoft (US), and Amazon (US).

Key Topics Covered:

1 Introduction

2 Research Methodology

3 Executive Summary

4 Premium Insights
4.1 Attractive Opportunities in the Artificial Intelligence in Supply Chain Market
4.2 Artificial Intelligence in Supply Chain Market, By Processor
4.3 Artificial Intelligence in Supply Chain Market for Fleet Management Application, By Technology
4.4 Artificial Intelligence in Supply Chain Market in APAC, By Application
4.5 Artificial Intelligence in Supply Chain Market, By Country

5 Market Overview
5.1 Introduction
5.2 Market Dynamics
5.2.1 Drivers
5.2.1.1 Growth of Big Data
5.2.1.2 Demand for Greater Visibility and Transparency in Supply Chain Data and Processes
5.2.1.3 Adoption of AI to Improve Consumer Services and Satisfaction
5.2.2 Restraints
5.2.2.1 Limited Number of AI Experts
5.2.3 Opportunities
5.2.3.1 Growing Impact of Cloud-Based Supply Chain Solutions
5.2.3.2 Increasing Demand for Intelligent Business Process and Automation
5.2.3.3 Improving Operational Efficiency in Manufacturing Industry
5.2.4 Challenges
5.2.4.1 Difficulties in Data Integration From Multiple Sources
5.2.4.2 Concerns Regarding Data Privacy
5.3 Case Studies
5.3.1 A Leading Luxury Vehicles Manufacturer Employed IBM Watson to Improve Critical Parts Management
5.3.2 Splice Machine Partners With Intrigo to Provide Order Promising and Scheduling Solution for Infinera
5.3.3 UPS Chatbot Now Available VIA the Google Assistant
5.3.4 Panalpina Engaged With Clearmetal for Predictive Logistics
5.3.5 Cummins Using Llamasoft Demand Guru for Demand Modelling

6 Artificial Intelligence in Supply Chain Market, By Offering
6.1 Introduction
6.2 Hardware
6.2.1 Processors
6.2.1.1 MPU
6.2.1.2 GPU
6.2.1.3 FPGA
6.2.1.4 ASIC
6.2.2 Memory
6.2.3 Network
6.3 Software
6.3.1 AI Platforms
6.3.1.1 Application Program Interface (API)
6.3.1.2 Machine Learning Framework
6.3.2 AI Solutions
6.4 Services
6.4.1 Deployment & Integration
6.4.2 Support & Maintenance

7 Artificial Intelligence in Supply Chain Market, By Technology
7.1 Introduction
7.2 Machine Learning
7.2.1 Supervised Learning
7.2.2 Unsupervised Learning
7.2.3 Reinforcement Learning
7.2.4 Others
7.3 Natural Language Processing (NLP)
7.4 Context-Aware Computing
7.5 Computer Vision

8 Artificial Intelligence in Supply Chain Market, By Application
8.1 Introduction
8.2 Fleet Management
8.3 Supply Chain Planning
8.4 Warehouse Management
8.5 Virtual Assistant
8.6 Risk Management
8.7 Freight Brokerage
8.8 Others

9 Artificial Intelligence in Supply Chain Market, By Industry
9.1 Introduction
9.2 Automotive
9.3 Aerospace
9.4 Manufacturing
9.5 Retail
9.6 Healthcare
9.7 Consumer-Packaged Goods
9.8 Food & Beverages
9.9 Others

10 Geographic Analysis
10.1 Introduction
10.2 North America
10.2.1 US
10.2.2 Canada
10.2.3 Mexico
10.3 Europe
10.3.1 Germany
10.3.2 UK
10.3.3 France
10.3.4 Italy
10.3.5 Spain
10.3.6 Rest of Europe
10.4 APAC
10.4.1 China
10.4.2 Japan
10.4.3 South Korea
10.4.4 India
10.4.5 Rest of APAC
10.5 Rest of the World
10.5.1 Middle East and Africa
10.5.2 South America

11 Competitive Landscape
11.1 Introduction
11.2 Market Ranking Analysis
11.3 Competitive Situations and Trends
11.3.1 Product Launches (2016-2018)
11.3.2 Agreements, Partnerships, Collaborations, & Contracts (2017-2018)
11.3.3 Mergers & Acquisitions (2016-2018)
11.3.4 Expansion (2016-2018)

12 Company Profiles
12.1 Key Players
12.1.1 Nvidia
12.1.2 IBM
12.1.3 Intel
12.1.4 Xilinx
12.1.5 Samsung Electronics
12.1.6 Micron Technology
12.1.7 Microsoft
12.1.8 Amazon
12.1.9 SAP
12.1.10 Oracle
12.1.11 Logility
12.1.12 Llamasoft, Inc.
12.1.13 Clearmetal
12.1.14 Splice Machine
12.1.15 Cainiao Network (Alibaba)
12.1.16 Fedex
12.1.17 Deutsche Post AG DHL
12.2 Other Companies
12.2.1 Fraight AI
12.2.2 C. H.Robinson
12.2.3 E2open
12.2.4 Relex Solution
12.2.5 Teknowlogi
12.2.6 Presenso