A team involved in preparing this Artificial Intelligence in Supply Chain market research report has kept certain things into focus that include the minds of target markets, feelings, preferences, attitudes, convictions and value systems. With a formalised and managerial approach, it is been assured that all the above mentioned factors are understood well and explored neatly in the report. This Artificial Intelligence in Supply Chain report also endows with the complete overview of the market that deals with the various aspects such as product definition, market segmentation, and the prevailing vendor landscape. In addition, it recognizes and analyses the emerging trends along with major driving factors, challenges and opportunities in the market for ICT industry.
This Artificial Intelligence in Supply Chain market report utilizes excellent research methodology which focuses on market share analysis and key trend analysis. A data triangulation method has been utilized for this purpose which has plentiful components such as data mining, analysis of data variable effect on the market, and primary or industry expert validation. Not to mention, large sample sizes have been exploited for the collection of data and info in this Artificial Intelligence in Supply Chain report. Market analysis covered here suits the requirements of small, medium as well as large size of businesses. Few more data models employed for the research methodology are merchant positioning grid, market time line analysis, market overview and guide, company positioning grid, company market share analysis, standards of measurement, thorough analysis and vendor share analysis.
Leading Players of Global Artificial Intelligence in Supply Chain Market are 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, 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.
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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Artificial Intelligence (AI) in supply chain is a creation of wise and smart machines that work, respond and react like people. It is utilized to enhance the proficiency of day by day undertakings. Advancing innovation, selection of robots and drones, driverless tractors, crop health checking, and automated water system framework are a part of the applications that credited to the high development of the global artificial intelligence in supply chain AIS showcase. Highly proficient yield examination is offered by drones and software programming advancements, for example, radars and GPS framework, empower to reduce weight on existing stressed workforce. In addition, remote detecting systems are also used to view the quality and yield creating capacity of a farming area.
The artificial intelligence in supply chain is a field holds secure development prospects, inferable from which, the key players are concentrating on building up an incorporated arrangement including equipment and programming. Moreover, to grow their client achieve, a few merchants have teamed up with wholesalers and end clients for item appropriation. The expanding conspicuousness of parallel preparing applications is prompting expanded selection of the innovation in logical teaches, for example, counterfeit consciousness and information science. Associations are using counterfeit measures to extricate significant insights of information for giving creative items and enhancing client encounter; in this manner, expanding income openings.
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.
Recent Industry Developments
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.
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.
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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
- Market opportunity
PART 09: CUSTOMER LANDSCAPE
PART 10: REGIONAL LANDSCAPE
- Geographical segmentation
- Regional comparison
- North America
- South America
- Market opportunity
PART 11: DECISION FRAMEWORK
PART 12: DRIVERS AND CHALLENGES
- Market drivers
- Market challenges
PART 13: MARKET TRENDS
PART 14: VENDOR LANDSCAPE
- Landscape disruption
PART 15: VENDOR ANALYSIS
- Vendors covered
- Vendor classification
- Market positioning of vendors
PART 16: APPENDIX
- List of abbreviations
See the complete table of contents and list of exhibits, as well as selected illustrations and example pages from this report.
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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
- Consumer-packaged goods,
- Food & beverages and others
Based on offering
- Software and
- 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).
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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