Global Artificial Intelligence in Supply Chain Market Size study, by Offering, by Technology, by Application, by End Use, and Regional Forecasts 2022-2032.

The global Artificial Intelligence in Supply Chain market was valued at USD 5.06 billion in 2023 and is projected to expand with a significant compound annual growth rate (CAGR) of 38.9% during the forecast period of 2024-2032. The remarkable growth trajectory of this market is primarily driven by the increasing need to streamline supply chains, optimize operational efficiency, and reduce costs across industries.

Artificial Intelligence (AI) solutions are revolutionizing supply chain management by automating repetitive tasks, analyzing large datasets, and providing actionable insights. E-commerce's rapid evolution has further necessitated the use of AI in inventory forecasting, demand planning, and logistics optimization to cater to fast-paced consumer needs. Additionally, AI's integration with IoT sensors and cloud computing platforms is facilitating real-time data collection and analysis, significantly enhancing supply chain agility.

Several industries, including automotive and consumer goods, are experiencing benefits through AI-powered tools that improve transportation planning, warehouse management, and order fulfillment processes. For instance, collaborations like IBM's recent AI solutions for retail with SAP SE are aimed at optimizing store-level assortments and enabling precise demand forecasts.

North America currently dominates the market, with an estimated share of 38.4% in 2023, driven by advancements in AI and technology adoption in supply chain operations. Meanwhile, the Asia Pacific region is anticipated to register the fastest CAGR, fueled by the growing adoption of AI tools in booming e-commerce markets like China and India. Europe is also witnessing significant traction, particularly in countries such as Germany and France, which are emphasizing Industry 4.0 and sustainability initiatives.

The robust market competition, characterized by constant innovation and merger activities, is propelling technological advancements in predictive maintenance and AI-integrated tools for logistics. However, high implementation costs and the need for specialized skills in AI adoption may present challenges in certain regions.

Major market players include IBM Corporation, SAP SE, Microsoft Corporation, and NVIDIA Corporation, among others. These companies continue to focus on collaborations, R&D investments, and acquisitions to strengthen their market presence and cater to an expanding customer base.

The detailed segmentation and regional insights presented in this study outline the market's comprehensive growth trajectory over the forecast years.

Major market players included in this report are:

• Advanced Micro Devices, Inc.
• Alibaba.com
• Amazon.com, Inc.
• Deutsche Post DHL Group
• FedEx
• International Business Machines Corporation
• Intel Corporation
• Microsoft Corporation
• NVIDIA Corporation
• Oracle Corporation
• Samsung
• SAP SE
• Vitesco Technologies GmbH
• Lenovo
• Blue Yonder Group, Inc.

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

By Offering

• Hardware
• Software
• Services

By Technology

• Machine Learning
• Computer Vision
• Natural Language Processing
• Context-Aware Computing
• Others

By Application

• Supply Chain Planning
• Warehouse Management
• Fleet Management
• Virtual Assistant
• Risk Management
• Inventory Management
• Planning & Logistics

By End Use

• Manufacturing
• Food and Beverages
• Healthcare
• Automotive
• Aerospace
• Retail
• Consumer-Packaged Goods
• Others

By Region:

• North America
• U.S.
• Canada
• Mexico
• Europe
• UK
• Germany
• France
• Asia Pacific
• China
• India
• Japan
• Australia
• South Korea
• Latin America
• Brazil
• Middle East & Africa
• UAE
• South Africa
• KSA

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.