Global Artificial Intelligence In Supply Chain Market
Market Size in USD Billion
CAGR :
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 Forecast Period |
2023 –2029 |
 Market Size (Base Year) |
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 Market Size (Forecast Year) |
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 CAGR |
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Global Artificial Intelligence in Supply Chain Market, By Offering (Hardware, Software and Services), Technology (Machine Learning, Natural Language Processing, Context-Aware Computing and Computer Vision), Application (Fleet Management, Supply Chain Planning, Warehouse Management, Virtual Assistant, Risk Management, Freight Brokerage and Others), Industry (Automotive, Aerospace, Retail, Manufacturing, Healthcare, Consumer-Packaged Goods and Food and Beverages), Country (U.S., Canada, Mexico, Brazil, Argentina, Rest of South America, Germany, France, Italy, U.K., Belgium, Spain, Russia, Turkey, Netherlands, Switzerland, Rest of Europe, Japan, China, India, South Korea, Australia, Singapore, Malaysia, Thailand, Indonesia, Philippines, Rest of Asia-Pacific, U.A.E, Saudi Arabia, Egypt, South Africa, Israel, Rest of Middle East and Africa) Industry Trends and Forecast to 2029
Market Analysis and Insights of Artificial Intelligence in Supply Chain Market
Surge in the rate of penetration of internet especially in the developing economies, growing focus on improving organizational performance and operational efficiency and rising adoption of advanced technologies such as artificial intelligence by the small and medium scale enterprises are the major factors attributable to the growth of the artificial intelligence in supply chain market. Data Bridge Market Research analyses that the artificial intelligence in supply chain market will exhibit a CAGR of 8.60% for the forecast period of 2022-2029. Therefore, the artificial intelligence in supply chain market value would stand tall by USD 54.51 million by 2029.
Artificial intelligence in supply chain helps in improving the overall supply chain performance by using cognitive predictions and recommendations on optimal actions. Artificial intelligence is used in supply chain applications to automate the processes such as allocating resources, assigning work to people and so on.
Rising digitization of the economies especially the emerging ones will emerge as the major market growth driving factor. Surging demand for greater visibility and transparency in the supply chain and logistics data, growing generation of high amount of data and information, rising adoption by small and medium scale enterprises and strengthening IT industry in developing economies such as India and China will further aggravate the growth of the market. Rising proliferation of cloud based services and ever-growing set of favourable government regulations are some other factors bolstering the growth of the market.
However, lack of technological expertise in underdeveloped and developing economies will act as growth restraints for the market. Also, lack of workforce and the increasing cost for the same will yet again hamper the market growth rate. Lack of strong infrastructural facilities in the backward economies and complexities associated with the coding of artificial intelligence will also challenge the market growth rate.
This artificial intelligence in supply chain market report provides details of new recent developments, trade regulations, import export analysis, production analysis, value chain optimization, market share, impact of domestic and localised market players, analyses opportunities in terms of emerging revenue pockets, changes in market regulations, strategic market growth analysis, market size, category market growths, application niches and dominance, product approvals, product launches, geographical expansions, technological innovations in the market. To gain more info on artificial intelligence in supply chain market contact Data Bridge Market Research for an Analyst Brief, our team will help you take an informed market decision to achieve market growth.
Global Artificial Intelligence in Supply Chain Market Scope and Market Size
The artificial intelligence in supply chain market is segmented on the basis of offering, technology, application and industry. The growth amongst the different segments helps you in attaining the knowledge related to the different growth factors expected to be prevalent throughout the market and formulate different strategies to help identify core application areas and the difference in your target market.
- Artificial intelligence in supply chain market on the basis of offering has been segmented hardware, software and services.
- Based on technology, the artificial intelligence in supply chain market has been segmented into machine learning, natural language processing, context-aware computing and computer vision.
- On the basis of application, the artificial intelligence in supply chain market has been segmented fleet management, supply chain planning, risk management, warehouse management, virtual assistant, freight brokerage and others.
- On the basis of industry, the artificial intelligence in supply chain market has been segmented automotive, aerospace, manufacturing, retail, healthcare, consumer-packaged goods and food and beverages.
Artificial Intelligence in Supply Chain Market Country Level Analysis
The artificial intelligence in supply chain market is analysed and market size, volume information is provided by country, offering, technology, application and industry as referenced above.
The countries covered in the artificial intelligence in supply chain market report are U.S., Canada and Mexico in North America, Germany, France, U.K., Netherlands, Switzerland, Belgium, Russia, Italy, Spain, Turkey, Rest of Europe in Europe, China, Japan, India, South Korea, Singapore, Malaysia, Australia, Thailand, Indonesia, Philippines, Rest of Asia-Pacific (APAC) in the Asia-Pacific (APAC), Saudi Arabia, U.A.E, Israel, Egypt, South Africa, Rest of Middle East and Africa (MEA) as a part of Middle East and Africa (MEA), Brazil, Argentina and Rest of South America as part of South America.
North America dominates the artificial intelligence in supply chain market and will continue to flourish its trend of dominance during the forecast period owing to the major presence of key players along with the presence of developed economies focusing on enhancing the existing solutions in the supply chain space. Asia-Pacific will continue to undergo substantial gains during the forecast period and will score the highest CAGR. This is because of the presence of young and tech-savvy population in this region and growing proliferation of internet of things (IoT).
The country section of the artificial intelligence in supply chain market report also provides individual market impacting factors and changes in regulation in the market domestically that impacts the current and future trends of the market. Data points such as consumption volumes, production sites and volumes, import export analysis, price trend analysis, cost of raw materials, down-stream and upstream value chain analysis are some of the major pointers used to forecast the market scenario for individual countries. Also, presence and availability of global brands and their challenges faced due to large or scarce competition from local and domestic brands, impact of domestic tariffs and trade routes are considered while providing forecast analysis of the country data.
Competitive Landscape and Artificial Intelligence in Supply Chain Market Share Analysis
The artificial intelligence in supply chain market competitive landscape provides details by competitor. Details included are company overview, company financials, revenue generated, market potential, investment in research and development, new market initiatives, global presence, production sites and facilities, production capacities, company strengths and weaknesses, product launch, product width and breadth, application dominance. The above data points provided are only related to the companies’ focus related to artificial intelligence in supply chain market.
Some of the major players operating in the artificial intelligence in supply chain market Amazon Web Services, Inc., project44., Deutsche Post AG, FedEx, GENERAL ELECTRIC, Google LLC, IBM, Intel Corporation, Coupa Software Inc.., Micron Technology, Inc., Microsoft, NVIDIA Corporation, Oracle., SAP SE, SAMSUNG, Xilinx, Fraight AI, C.H. Robinson Worldwide, Inc., E2open, LLC., RELEX Solutions, SKF Group, Cainiao Network, Splice Machine and American Software, Inc., among others.
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Research Methodology
Data collection and base year analysis are done using data collection modules with large sample sizes. The stage includes obtaining market information or related data through various sources and strategies. It includes examining and planning all the data acquired from the past in advance. It likewise envelops the examination of information inconsistencies seen across different information sources. The market data is analysed and estimated using market statistical and coherent models. Also, market share analysis and key trend analysis are the major success factors in the market report. To know more, please request an analyst call or drop down your inquiry.
The key research methodology used by DBMR research team is data triangulation which involves data mining, analysis of the impact of data variables on the market and primary (industry expert) validation. Data models include Vendor Positioning Grid, Market Time Line Analysis, Market Overview and Guide, Company Positioning Grid, Patent Analysis, Pricing Analysis, Company Market Share Analysis, Standards of Measurement, Global versus Regional and Vendor Share Analysis. To know more about the research methodology, drop in an inquiry to speak to our industry experts.
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