PUBLISHER: Orion Market Research | PRODUCT CODE: 1363954
PUBLISHER: Orion Market Research | PRODUCT CODE: 1363954
Title: Global AI in Supply Chain Market Size, Share & Trends Analysis Report by Technology (Machine Learning (ML), Natural Language Processing (NLP), Context-Aware Computing, and Computer Vision), by Application (Fleet Management, Supply Chain Planning, Warehouse Management, Virtual Assistant, Risk Management, Freight Brokerage, and Others), and by End-User (Automotive, Aerospace, Manufacturing, Retail, Healthcare, Consumer-packaged Goods, Food and Beverages, and Others),Forecast Period (2023-2030).
The global AI in Supply Chain market is anticipated to grow at a CAGR of 38.8% during the forecast period (2023-2030). The market's growth is attributed to the increasing demand for AI knowledge in supply chain. There is an increased need for personnel who possess knowledge and experience in AI technologies and how to apply them to supply chain processes. Companies are recognizing the necessity of improving the AI-related skills of their employees. This necessitates having a workforce that understands AI technologies and their application in supply chain operations. Thus, it is essential for businesses to upskill their staff in AI-related competencies. As a result, the market players are coming up with new products to cater the demand for enhance their logistical capabilities of the organizations around the globe. For instance, in May 2023, SAP SE launched SAP Business AI, was its response. In partnership with Microsoft, the business combines its solutions with Microsoft 365 Copilot and Azure OpenAI to help clients increase their logistical skills and prepare staff to handle logistical challenges in the future.
The global AI in supply chain market is segmented on the technology, application, and end-user. Based on the technology, the market is sub-segmented into ML, NLP, context-aware computing, and computer vision. Based on the application, the market is sub-segmented into fleet management, supply chain planning, warehouse management, virtual assistant, risk management, freight brokerage, and others. Furthermore, on the basis of end-user, the market is sub-segmented into automotive, aerospace, manufacturing, retail, healthcare, consumer-packaged goods, food and beverages, and others. Among the technology, ML sub-segment is anticipated to hold a considerable share of the market owing to various advantages offered by supply chain organizations, including cost savings, risk reduction, enhanced forecasting, more rapid deliveries, and improved customer service.
Among the application, the supply chain planning sub-segment is expected to hold a considerable share of the market. The growth in this segment can be attributed to the increasing complexity of supply chains. AI plays a crucial role in addressing this complexity by providing real-time visibility and predictive analytics. This capability enables businesses to make well-informed decisions in the face of highly intricate and global supply chains, which involve multiple partners, suppliers, and logistics routes. Thus, to cater to the demand for enhanced supply chain planning, market players have introduced innovative products. For instance, in November 2022, 3SC Solutions launched a SCAI, or intelligent supply chain planning and execution platform, aids companies in optimizing the supply chains for their products and services. The entire platform assists companies in creating synchronized and resilient supply chains in addition to improving efficiency, boosting profitability, cutting waste, and operating more sustainably.
The global AI in supply chain market is further segmented based on geography including North America (the US, and Canada), Europe (UK, Italy, Spain, Germany, France, and the Rest of Europe), Asia-Pacific (India, China, Japan, South Korea, and Rest of Asia), and the Rest of the World (the Middle East & Africa, and Latin America). Among these, Asia-Pacific is anticipated to hold a prominent share of the market around the globe, owing to the wide emergence of deep learning and NLP technologies in applications related to manufacturing, retail, and automotive.
North America is anticipated to grow at a considerable CAGR over the forecast period. Regional growth is attributed to route optimization. Utilizing real-time information on traffic, weather, and transportation costs, ML is utilized to optimize shipping routes and schedules. This reduces the cost of transportation and improves delivery reliability. For instance, according to Cross River Therapy, in July 2023, ML is a subset of AI that involves training algorithms to make predictions or decisions based on data. Over the past two years, 90% of the globe's data has been created, and ML is an essential tool for analyzing this data.
ML algorithms are being used in a variety of industries, including finance, healthcare, and transportation, to improve safety, efficiency, and customer experience. For example, it is used to detect fraudulent transactions in finance, develop personalized treatments in healthcare, and power self-driving cars in transportation. Additionally, ML algorithms are also used to analyze text data in NLP and generate insights into customer sentiment. Thus, it has become an integral part of the development of AI applications in many industries.
The major companies serving the AI in supply chain market include Amazon Web Services, Inc., FedEx Corp., General Electric Co., Google, IBM Corp. and others. The market players are considerably contributing to the market growth by the adoption of various strategies including mergers and acquisitions, partnerships, collaborations, funding, and new product launches, to stay competitive in the market. For instance, in May 2023, Resilinc, partnered with SEMI, the industry association serving the global electronics manufacturing and design supply chain. Through the partnership, Resilinc collaborate with SEMI to provide its more than 2,500 members with resources for achieving greater supply chain visibility and transparency and ultimately enhance the resilience of the entire semiconductor value chain.