Artificial intelligence (AI) in the supply chain possesses several essential possessions that contribute to its significance in the artificial intelligence in the supply chain market. These properties include advanced data analytics, machine learning algorithms, automation, and predictive capabilities. AI enables real-time analysis of large volumes of data, leading to improved decision-making, enhanced efficiency, and cost optimization. It facilitates demand forecasting, inventory management, demand-supply matching, and route optimization. Additionally, AI-driven supply chain solutions offer greater visibility, transparency, and traceability, ensuring compliance and mitigating risks. These properties drive the adoption of AI in the supply chain market, transforming traditional supply chain operations and delivering tangible benefits to businesses.
According to Data Bridge Market research, Artificial Intelligence in Supply Chain Market will exhibit a CAGR of 8.60% for the forecast period of 2022-2029. Therefore, artificial intelligence in supply chain market value would stand tall at USD 54.51 million by 2029.
“Demand for greater visibility and transparency in supply chain and logistics data serves to drive the market”
The increasing demand for greater visibility and transparency in supply chain and logistics data is a significant driver for artificial intelligence in the supply chain market. Businesses and consumers alike seek real-time tracking, traceability, and accurate insights into their supply chain operations. Artificial intelligence technologies, such as machine learning and data analytics, enable organizations to process vast amounts of data, identify patterns, and generate actionable insights. Through leveraging AI, companies can enhance supply chain efficiency, optimize inventory management, mitigate risks, and improve customer satisfaction. The pressing need for visibility and transparency is a strong catalyst for adopting AI in the supply chain sector.
What restraints the growth of artificial intelligence in supply chain market?
“Lack of technological expertise in underdeveloped and developing economies”
The lack of technological expertise in underdeveloped and developing economies significantly restraints artificial intelligence in the supply chain market. These regions often face limited resources, infrastructure, and skilled workforce challenges. Implementing and adopting advanced AI technologies in the supply chain requires specialized knowledge and technical expertise, which may be lacking in these economies. This creates a barrier to the widespread adoption of AI solutions, hindering market growth in these regions and creating a technological gap between developed and developing economies in the supply chain domain.
Segmentation: Artificial Intelligence in Supply Chain Market
The artificial intelligence in supply chain market is segmented on the basis of offering, technology, application, and industry.
- On the basis of offering, the artificial intelligence in supply chain market is segmented into hardware, software, and services.
- On the basis of 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.
Regional Insights: North America dominates the artificial intelligence in supply chain market
North America's dominance in the artificial intelligence in the supply chain market is attributed to its major presence of key players and developed economies that prioritize enhancing existing solutions. This trend is expected to continue during the forecast period, further strengthening North America's position in the market.
Asia-Pacific is projected to experience significant growth and achieve the highest compound annual growth rate (CAGR) in the artificial intelligence in the supply chain market. This can be attributed to factors such as a young and tech-savvy population in the region and the increasing adoption of Internet of Things (IOT) technologies that drive the demand for advanced supply chain solutions.
To know more about the study visit, https://www.databridgemarketresearch.com/reports/global-artificial-intelligence-in-supply-chain-market
The Prominent Key Players Operating in the Artificial Intelligence in Supply Chain Market Include:
- Amazon Web Services, Inc. (U.S.)
- project44 (U.S.)
- Deutsche Post AG – (Germany)
- FedEx (U.S.)
- GENERAL ELECTRIC (U.S.)
- Google LLC (U.S.)
- IBM (U.S.)
- Intel Corporation (U.S.)
- Coupa Software Inc. (U.S.)
- Micron Technology, Inc. (U.S.)
- Microsoft (U.S.)
- NVIDIA Corporation (U.S.)
- Oracle (U.S.)
- SAP SE (Germany)
- SAMSUNG (South Korea)
- Xilinx – (U.S.)
- Fraight AI – (U.S.)
- C.H. Robinson Worldwide, Inc. – (U.S.)
- E2open, LLC – (U.S.)
- RELEX Solutions (Finland)
- SKF Group (Sweden)
- Cainiao Network (China)
- Splice Machine (U.S.)
- American Software, Inc. (U.S.)
Above are the key players covered in the report, to know about more and exhaustive list of artificial intelligence in supply chain market companies contact, https://www.databridgemarketresearch.com/contact
Research Methodology: Global Artificial Intelligence in Supply Chain Market
Data collection and base year analysis are done using data collection modules with large sample sizes. The market data is analyzed and estimated using market statistical and coherent models. In addition, market share analysis and key trend analysis are the major success factors in the market report. 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. Apart from this, data models include Vendor Positioning Grid, Market Time Line Analysis, Market Overview and Guide, Company Positioning Grid, Company Market Share Analysis, Standards of Measurement, global vs Regional and Vendor Share Analysis. Please request analyst call in case of further inquiry.
