Global Artificial Intelligence in Supply Chain Market: In-Depth Market Research Report By 2025 and top players are Amazon, SAP, Oracle, Logility, LLamasoft, Inc., NVIDIA, IBM, Intel Corporation, Xilinx, Samsung Electronics, Samsung Electronics America

The Global Artificial Intelligence in Supply Chain Market research report provides a comprehensive study on production capacity, consumption, import and export for all major regions across the globe. This Artificial Intelligence in Supply Chain market Report cover strategic profiling of key players in the market, comprehensively analyzing their core competencies, and drawing a competitive landscape for the market. This analysis gives an examination of various segments that are relied upon to witness the quickest development amid the estimate forecast frame. The data and the information regarding the Artificial Intelligence in Supply Chain industry are taken from reliable sources such as websites, annual reports of the companies, journals, and others and were checked and validated by the market experts.

The Global Artificial Intelligence in Supply Chain Market is expected to reach USD 10,787.2 million by 2025 from USD 21.21 million in 2017 and is projected to grow at a CAGR of 8.1% in the forecast period of 2018 to 2025.

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KEY HIGHLIGHTS OF THE ARTIFICIAL INTELLIGENCE IN SUPPLY CHAIN MARKET REPORT:

• Get enlightened information available on the Artificial Intelligence in Supply Chain market worldwide.

• Identify growth in various segments and investment opportunities. Benchmark fulfillment adjacent the key adversary.

• The main criterion related to Artificial Intelligence in Supply Chain industry area including the overall structure of the product, numbers of applications, price, demand, and supply are enfolded in this report.

• The research of emerging Artificial Intelligence in Supply Chain market section and extant industry segments will aid the investors or novice in formulating and developing business strategies.

• Facilitates decision making in view of noteworthy and gauging information also the drivers and limitations available of the market.

• Global Artificial Intelligence in Supply Chain Market share assessments for the regional and country level segments.

TABLE OF CONTENTS

PART 01: EXECUTIVE SUMMARY

PART 02: SCOPE OF THE REPORT

PART 03: RESEARCH METHODOLOGY

PART 04: MARKET LANDSCAPE

• Market ecosystem
• Market characteristics
• Market segmentation analysis

PART 05: PIPELINE ANALYSIS

• Pipeline analysis

PART 06: MARKET SIZING

• Market definition
• Market sizing
• Market size and forecast

PART 07: FIVE FORCES ANALYSIS

• Bargaining power of buyers
• Bargaining power of suppliers
• Threat of new entrants
• Threat of substitutes
• Threat of rivalry
• Market condition

PART 08: MARKET SEGMENTATION

• Segmentation
• Comparison
• Market opportunity

PART 09: CUSTOMER LANDSCAPE

PART 10: REGIONAL LANDSCAPE

• Geographical segmentation
• Regional comparison
• North America
• South America
• Europe
• MEA
• APAC
• Market opportunity

PART 11: DECISION FRAMEWORK

PART 12: DRIVERS AND CHALLENGES

• Market drivers
• Market challenges

PART 13: MARKET TRENDS

PART 14: VENDOR LANDSCAPE

• Overview
• Landscape disruption

PART 15: VENDOR ANALYSIS

• Vendors covered
• Vendor classification
• Market positioning of vendors

PART 16: APPENDIX

• List of abbreviations

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COMPANIES COVERED

• NVIDIA,
• IBM,
• Intel Corporation,
• Xilinx,
• Samsung Electronics,
• Samsung Electronics America,
• Micron Technology,
• Microsoft,
• Amazon,
• SAP,
• Oracle,
• Logility,
• LLamasoft, Inc.,
• ClearMetal,
• Splice Machine,
• Cainiao Networks,
• FedEx,
• DHL,
• C.H. Robinson,
• E2open,
• RELEX Solutions,
• Teknowlogi,
• Presenso,
• Fraight AI,
• FedEx Supply Chain,
• Deutsche Post,
• Alibaba Group,
• SoftBank Group,
• Baidu, Inc.,
• Salesforce,
• Interactions LLC,
• Lexalytics, Inc.,
• FedEx Express Canada,
• Next IT,
• RetailNext,
• Sentient Technologies,
• ViSenze - AI for Visual Commerce,
• Amazon Web Services and others.

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Market Segmentation

Based on application

• Fleet management,
• Supply chain planning,
• Warehouse management,
• Virtual assistant,
• Risk management,
• Freight brokerage and others

Based on technology

• Machine learning,
• Natural language processing (NLP),
• Context-aware computing and
• Computer vision

Based on industry

• Automotive,
• Aerospace,
• Manufacturing,
• Retail,
• Healthcare,
• Consumer-packaged goods,
• Food & beverages and others

Based on offering

• Hardware,
• Software and
• Services

By Geography

• Asia Pacific (China, South Korea, Japan, India, Australia, Singapore, Thailand, Indonesia, Malaysia, Philippines, Rest of Asia-Pacific).

• North America (US, Canada, Mexico).

• Europe (Russia, Turkey, Belgium, Netherlands, Switzerland, Spain, France, Germany, Italy, UK, Rest of Europe.

• South America (Brazil, Argentina, Rest of South America).

• Middle East and Africa (South Africa, Egypt, Saudi Arabia, United Arab Emirates, Israel, Rest of Middle East and Africa).

Competitive Analysis

The global artificial intelligence in supply chain market is fragmented and the major players have used various strategies such as new product launches, expansions, agreements, joint ventures, partnerships, acquisitions, and others to increase their footprints in this market in order to sustain in long run. The report includes market shares of artificial intelligence in supply chain market for global, Europe, North America, Asia Pacific and South America.

In 2016 artificial intelligence and machine learning emerging as the next big technology has seen a race for artificial intelligence, with a number of acquisitions and large technology vendors such as IBM, Google and Amazon are launching a new artificial intelligence-enabled product.

In 2017, Teknowlogi Launches a first cloud-based solution built on artificial intelligence for the logistics industry. It is a next-generation platform category, representing a much-needed advancement for traditional industry logistics system.

Market Drivers and Restraints:

• Growth of big data

• Demand for greater visibility and transparency in supply chain data and processes

• Adoption of AI to improve consumer services and satisfaction.

• High Information and data storage capacity

• High computing power and parallel processing capabilities

• Lack of people power

• Data inefficiency in building proper AI algorithms.

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