Global Artificial Intelligence (AI) in Supply Chain and Logistics Market Size study, by Type (Artificial Neural Networks, Machine Learning, Others), by Application (Inventory Control and Planning, Transportation Network Design, Purchasing and Supply Manag

Global Artificial Intelligence (AI) in Supply Chain and Logistics Market Size study, by Type (Artificial Neural Networks, Machine Learning, Others), by Application (Inventory Control and Planning, Transportation Network Design, Purchasing and Supply Management, Demand Planning and Forecasting, Others), and Regional Forecasts 2022-2032

The global Artificial Intelligence (AI) in Supply Chain and Logistics Market is valued at approximately USD 1713 million in 2023 and is anticipated to grow with a healthy growth rate of more than 10.1% over the forecast period 2024-2032. Artificial intelligence (AI) in supply chain and logistics encompasses the use of AI techniques and technologies to enhance the efficiency, effectiveness, and sustainability of supply chain operations. By leveraging AI, supply chain and logistics professionals can address complex challenges, automate tasks, optimize decision-making, and ultimately create value. AI's application spans various facets of supply chain and logistics, including demand forecasting, inventory management, production planning, transportation routing, warehouse management, order fulfilment, customer service, and risk management.

The burgeoning volume of big data, coupled with the need for greater visibility and transparency in supply chain operations, are key drivers propelling market growth. The adoption of AI is further enhanced by its ability to elevate consumer services and satisfaction levels. Nonetheless, a notable challenge impeding market progress is the scarcity of expertise in AI technology. The demand for transparent and observable supply chain methodologies significantly drives the market. AI's integration within the logistics sector, particularly for autonomous data processing in areas like warehouse stock management, inventory management, product safety, and timely delivery, underscores its essential role in modern supply chains. Additionally, government regulations and initiatives promoting machine automation and AI computing further bolster market growth. However, the adoption of effective supply chain information solutions in developing countries is limited by several constraints, prompting government investments to raise awareness and integrate advanced technologies into business operations.

AI technologies in supply chain operations eliminate the need for human effort, resulting in substantial time and cost savings. This operational advantage is a crucial market driver, with large companies increasingly investing in machine automation to reduce future operating costs. Various end-user industries are leveraging AI applications in the supply chain market, contributing to the sector's growth. The increasing adoption of IoT devices and cloud computing services revolutionizes data processing, with big data technology already prevalent in the logistics industry. The trend towards supply chain automation through AI suggests continued demand for automated solutions.

North America dominates the AI in supply chain market, attributed to the presence of developed economies focused on enhancing existing supply chain solutions and key industry players. The Asia Pacific region is projected to experience the highest CAGR during the forecast period, driven by the adoption of deep learning and Natural Language Processing (NLP) technologies in automotive, retail, and manufacturing industries, along with the presence of major players in the AI ecosystem.

Major market players included in this report are:

IBM Corporation

Microsoft Corporation

Google LLC

Amazon Web Services (AWS)

Oracle Corporation

SAP SE

Nvidia Corporation

Intel Corporation

Cisco Systems, Inc.

Siemens AG

General Electric Company

Accenture plc

Splice Machine

PricewaterhouseCoopers (PwC)

Xilinx

The detailed segments and sub-segment of the market are explained below:

By Type:
• Artificial Neural Networks
• Machine Learning
• Others

By Application:
• Inventory Control and Planning
• Transportation Network Design
• Purchasing and Supply Management
• Demand Planning and Forecasting
• Others

By Region:

North America
• U.S.
• Canada

Europe
• UK
• Germany
• France
• Spain
• Italy
• ROE

Asia Pacific
• China
• India
• Japan
• Australia
• South Korea
• RoAPAC

Latin America
• Brazil
• Mexico
• RoLA

Middle East & Africa
• Saudi Arabia
• South Africa
• RoMEA

Years considered for the study are as follows:
• Historical year – 2022
• Base year – 2023
• Forecast period – 2024 to 2032

Key Takeaways:
• Market Estimates & Forecast for 10 years from 2022 to 2032.
• Annualized revenues and regional level analysis for each market segment.
• Detailed analysis of geographical landscape with Country level analysis of major regions.
• Competitive landscape with information on major players in the market.
• Analysis of key business strategies and recommendations on future market approach.
• Analysis of competitive structure of the market.
• Demand side and supply side analysis of the market.

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