세계의 물류 및 공급망 분야 AI 시장 규모 : 제공 제품별, 용도별, 최종사용자별, 지역 범위별 및 예측

AI In Logistics And Supply Chain Market Size And Forecast

AI In Logistics And Supply Chain Market size was valued at USD 4450.64 Million in 2024 and is projected to reach USD 65039.34 Million by 2032, growing at a CAGR of 46.50% from 2026 to 2032.

AI in logistics and supply chain is the application of artificial intelligence technologies such as machine learning, predictive analytics, and automation to the management of commodities, services, and information at various levels of the supply chain. AI improves decision-making by evaluating massive amounts of data from many sources, optimizing routes, controlling inventories, and forecasting demand. Applications include self-driving cars and drones for transportation, AI-powered chatbots for customer support, and automated warehousing operations for increased productivity. This technology enhances accuracy, lowers costs, and reduces human error in the logistics industry.

AI in logistics and supply chain management is rapidly expanding, driven by the growing demand for more flexible and responsive supply chains in industries such as e-commerce, manufacturing, and retailing. As AI advances, potential applications include improved supply chain visibility, real-time tracking, and predictive asset maintenance.

AI's ability to decrease risks, delays, and boost sustainability through resource optimization will be important in altering global logistics networks. The market for AI-powered solutions in this industry is predicted to expand rapidly, driven by the growing use of IoT, big data, and robotics in logistics operations.

Global AI In Logistics And Supply Chain Market Dynamics

The key market dynamics that are shaping the global AI In Logistics And Supply Chain Market include:

Key Market Drivers:

Increasing E-Commerce Adoption: The rapid growth in e-commerce, with US e-commerce sales expected to reach USD 870.8 Billion in 2021, up 14.2% from 2020, is pushing the demand for more efficient logistics and supply chain management. This spike presents complicated issues such as managing high-order quantities, ensuring timely deliveries, and handling returns. AI can assist address these difficulties by optimizing routes, automating warehouses, and forecasting demand, resulting in more efficient operations and more customer satisfaction.

Rising Demand for Supply Chain Visibility and Transparency: The rising need for supply chain visibility and transparency is driven by the need to manage disruptions, with the Business Continuity Institute projecting that 69% of firms would experience at least one supply chain disruption in 2021. Both organizations and consumers want real-time tracking to ensure smoother operations, faster problem resolution, and more consistent deliveries. AI provides the predictive skills and real-time data analytics required to improve visibility, decrease risks, and strengthen the overall supply chain resilience.

Need for Cost Reduction and Operational Efficiency: The need for cost reduction and operational efficiency is a fundamental driver in supply chain management, with U.S. company logistics expenditures expected to reach USD 1.63 Trillion in 2020, accounting for 7.4% of GDP, according to the CSCMP. Companies are increasingly depending on artificial intelligence (AI) to optimize processes, cut personnel costs, and streamline operations. AI increases efficiency through automation, predictive analytics, and inventory management, allowing firms to reduce costs while maintaining excellent service levels in a competitive market.

Key Challenges:

Limited Access to Quality Data: AI relies on high-quality, well-organized data to make accurate predictions and decisions. Many supply chains still work with fragmented or poorly formatted data, resulting in inadequate AI performance. Limited access to real-time, clean data makes it difficult for businesses to fully leverage AI's assurance, lowering its efficacy in optimizing operations.

Regulatory and Compliance Challenges: AI in logistics operates in a complicated regulatory environment that varies by region and industry. Adhering to many rules, such as those governing data privacy, labor legislation, and environmental requirements, can be difficult. Companies must verify that their AI systems adhere to numerous regulatory frameworks, which can hinder deployment and increase operational costs.

Data Privacy and Security Concerns: As AI systems rely on massive volumes of data, privacy and security are major concerns. As firms communicate sensitive information throughout the supply chain, the danger of data breaches grows. Stricter data standards and customer privacy expectations require enterprises to secure their data, which slows AI adoption and raises compliance costs.

Key Trends:

Predictive Analytics for Demand Forecasting: AI-powered predictive analytics is becoming an essential tool for anticipating demand throughout supply chains. AI assists businesses in better anticipating demand swings by studying past data and external factors, resulting in fewer stockouts and overstocking. This trend is motivated by the demand for more agile supply chains that can react to market developments in real-time, hence increasing customer satisfaction and lowering waste.

AI-Enhanced Last-Mile Delivery Optimization: AI is transforming last-mile delivery by optimizing routes, lowering fuel usage, and shortening delivery times. With the advent of e-commerce and consumer expectations for speedy, cost-effective shipping, businesses are turning to artificial intelligence to increase efficiency in the final leg of the delivery process. This trend is driven by the growing need to improve delivery speed and accuracy while lowering logistical costs.

AI-Driven Risk Management and Disruption Mitigation: AI is rapidly being utilized to predict and mitigate risks such as supply chain disruptions, natural disasters, and geopolitical incidents. AI may anticipate future interruptions and provide contingency preparations by analyzing multiple data sources. This trend is being driven by the increased complexity and internationalization of supply chains, which requires proactive risk management techniques to ensure smooth operations.

Integration of AI and Internet of Things (IoT): The integration of AI and the Internet of Things (IoT) is improving supply chain automation by enabling smarter and more connected logistics systems. IoT sensors collect real-time data from trucks, warehouses, and products, and AI analyzes this information to optimize operations. This trend is motivated by the desire for smarter, more efficient supply networks that can self-monitor and continuously improve.

Global AI In Logistics And Supply Chain Market Regional Analysis

Here is a more detailed regional analysis of the global AI In Logistics And Supply Chain Market:

North America:

North America is dominant in the AI In Logistics And Supply Chain Market. North America leads in AI adoption in logistics and supply chain management due to its advanced technological infrastructure, strong research and development (R&D) skills, and large number of early adopters. The region's well-established logistics sector, combined with a constant focus on efficiency and innovation, creates ideal conditions for AI solutions to thrive. According to the US Bureau of Labor Statistics, employment in logistics and supply chain management is expected to increase by 30% between 2020 and 2030, owing in part to the growing incorporation of AI technology.

Government support and industry partnerships are speeding up AI deployment in North America. AI-driven logistics optimization has already produced incredible results, with enterprises reporting a 15% cost savings and a 20% improvement in delivery times. The Canadian government's Strategic Innovation Fund, which has committed CAD 950 million (USD 700 Million) for AI research and development from 2023 to 2025, demonstrates the region's leadership in this field. These characteristics - significant investment, strong government support, and tangible advantages - are propelling AI adoption in North America's logistics and supply chain sectors, establishing the region as a global leader in efficiency and competitiveness.

Asia Pacific:

The Asia-Pacific area is seeing huge growth in AI adoption for logistics and supply chain applications, making it the world's fastest-growing market. This spike is being driven by strong economic growth, increasing e-commerce, and an urgent need to improve supply chain efficiency across complicated networks. According to the Asian Development Bank (ADB), the region's e-commerce sector is expected to reach $2.8 trillion by 2025, with a compound annual growth rate (CAGR) of 18.5%. This vast expansion in online retail is putting huge pressure on logistical networks, forcing businesses to use AI-powered solutions to handle the increasing complexity and transaction volumes. Countries with substantial logistics sectors, such as China and India, are leading the drive, with China reporting that 72% of its large logistics enterprises had already deployed AI by 2023, and the figure is predicted to exceed 85% by 2026.

The region's emphasis on cost reduction and operational efficiency accelerates AI adoption. AI-driven solutions are already demonstrating substantial benefits across the region, with Japanese enterprises reporting an 18% cost reduction and a 25% increase in inventory turnover by 2023. Investments in AI for logistics are also increasing, with Southeast Asia alone experiencing a 45% year-over-year rise in AI spending in 2023, which is expected to treble by 2026. These reasons - rapid e-commerce growth, pressure on supply chains, government initiatives, and demonstrable efficiency - are propelling Asia-Pacific AI adoption, establishing it as a global leader in innovative logistics solutions.

Global AI In Logistics And Supply Chain Market: Segmentation Analysis

The Global AI In Logistics And Supply Chain Market is Segmented on the basis of Offering, Application, End-User, And Geography.

AI In Logistics And Supply Chain Market, By Offering

• Hardware
• Software

Based on Offering, the market is bifurcated into Hardware, and Software. Software is the fastest-growing segment, driven by rising demand for AI-powered solutions like as predictive analytics, route optimization, and warehouse automation. As logistics organizations seek to improve efficiency and cut costs, AI-based software systems are fast gaining popularity. Hardware dominates market share since AI requires powerful computing infrastructure, sensors, and robotics to work well, notably in automated warehouses and transportation systems. Due to the dependency on physical infrastructure, hardware is an essential component of AI logistics integration.

AI In Logistics And Supply Chain Market, By Application

• Supply Chain Planning
• Warehouse Management
• Demand Forecasting
• Inventory Management

Based on Application, the market is segmented into Supply Chain Planning, Warehouse Management, Demand Forecasting, and Inventory Management. Warehouse management is the most dominating segment, as it includes a wide range of AI applications that improve operational efficiency, such as automated inventory tracking, robotic picking systems, and optimized storage solutions. The use of artificial intelligence in warehouse management is critical for optimizing operations and lowering costs, cementing its place as a vital market area. Demand forecasting is the fastest-growing segment, driven by the requirement for precise forecasts to satisfy consumer expectations and optimize inventory levels. Companies are increasingly using AI algorithms to analyze historical data and market trends, which improves their ability to predict demand fluctuations.

AI In Logistics And Supply Chain Market, By End-User

• Automotive
• Retail
• Food and Beverages
• Healthcare
• Manufacturing

Based on End-User, the market is segmented into Automotive, Retail, Food and Beverages, Healthcare, and Manufacturing. The automotive segment is currently dominating, thanks to the industry's emphasis on streamlining production processes, increasing supply chain efficiency, and integrating autonomous car technologies. The automotive industry relies extensively on artificial intelligence (AI) for inventory management, predictive maintenance, and logistical coordination, making it a critical market player. The retail segment is the fastest-growing, driven by e-commerce's spectacular development and the need for real-time inventory tracking, individualized customer experiences, and demand forecasting. Retailers are increasingly using AI-powered solutions to optimize operations, manage complex supply chains, and boost consumer happiness.

Key Players

The "Global AI In Logistics And Supply Chain Market" study report will provide valuable insight with an emphasis on the global market. The major players in the market are IBM Corporation, Microsoft Corporation, Google LLC, Amazon.com, Inc., Intel Corporation, Nvidia Corporation, Oracle Corporation, Samsung, and Lamasoft, Inc. The competitive landscape section also includes key development strategies, market share, and market ranking analysis of the above-mentioned players globally.

Our market analysis also entails a section solely dedicated to such major players wherein our analysts provide an insight into the financial statements of all the major players, along with product benchmarking and SWOT analysis. The competitive landscape section also includes key development strategies, market share, and market ranking analysis of the above-mentioned players globally.

• AI In Logistics And Supply Chain Market Recent Developments
• In March 2024, Oracle's new AI-powered supply chain execution capabilities, Oracle Smart Operations, will be available allowing businesses to boost factory output by increasing productivity, improving quality, minimizing downtime, and improving visibility across operations.
• In November 2023, IBM and Amazon expanded their relationship to assist businesses in implementing generative AI in their supply chains. They intend to provide a virtual assistant to help supply chain professionals optimize operations and cut expenses.

TABLE OF CONTENTS

1 INTRODUCTION OF GLOBAL AI IN LOGISTICS AND SUPPLY CHAIN MARKET

• 1.1 Overview of the Market
• 1.2 Scope of Report
• 1.3 Assumptions

2 EXECUTIVE SUMMARY

3 RESEARCH METHODOLOGY OF VERIFIED MARKET RESEARCH

• 3.1 Data Mining
• 3.2 Validation
• 3.3 Primary Interviews
• 3.4 List of Data Sources

4 GLOBAL AI IN LOGISTICS AND SUPPLY CHAIN MARKET OUTLOOK

• 4.1 Overview
• 4.2 Market Dynamics
  • 4.2.1 Drivers
  • 4.2.2 Restraints
  • 4.2.3 Opportunities
• 4.3 Porters Five Force Model
• 4.4. Value Chain Analysis

5 GLOBAL AI IN LOGISTICS AND SUPPLY CHAIN MARKET, BY OFFERING

• 5.1 Overview
• 5.2 Hardware
• 5.3 Software

6 GLOBAL AI IN LOGISTICS AND SUPPLY CHAIN MARKET, BY APPLICATION

• 6.1 Overview
• 6.2 Supply Chain Planning
• 6.3 Warehouse Management
• 6.4 Demand Forecasting
• 6.5 Inventory Management

7 GLOBAL AI IN LOGISTICS AND SUPPLY CHAIN MARKET, BY END-USER

• 7.1 Overview
• 7.2 Automotive
• 7.3 Retail
• 7.4 Food and Beverages
• 7.5 Healthcare
• 7.6 Manufacturing

8 GLOBAL AI IN LOGISTICS AND SUPPLY CHAIN MARKET, BY GEOGRAPHY

• 8.1 Overview
• 8.2 North America
  • 8.2.1 U.S.
  • 8.2.2 Canada
  • 8.2.3 Mexico
• 8.3 Europe
  • 8.3.1 Germany
  • 8.3.2 U.K.
  • 8.3.3 France
  • 8.3.4 Rest of Europe
• 8.4 Asia Pacific
  • 8.4.1 China
  • 8.4.2 Japan
  • 8.4.3 India
  • 8.4.4 Rest of Asia Pacific
• 8.5 Rest of the World
  • 8.5.1 Middle East and Africa
  • 8.5.2 South America

9 GLOBAL AI IN LOGISTICS AND SUPPLY CHAIN MARKET COMPETITIVE LANDSCAPE

• 9.1 Overview
• 9.2 Company Market Ranking
• 9.3 Key Development Strategies

10 COMPANY PROFILES

• 10.1 IBM Corporation
  • 10.1.1 Overview
  • 10.1.2 Financial Performance
  • 10.1.3 Product Outlook
  • 10.1.4 Key Developments
• 10.2 Microsoft Corporation
  • 10.2.1 Overview
  • 10.2.2 Financial Performance
  • 10.2.3 Product Outlook
  • 10.2.4 Key Developments
• 10.3 Google LLC
  • 10.3.1 Overview
  • 10.3.2 Financial Performance
  • 10.3.3 Product Outlook
  • 10.3.4 Key Developments
• 10.4 Amazon.com, Inc.
  • 10.4.1 Overview
  • 10.4.2 Financial Performance
  • 10.4.3 Product Outlook
  • 10.4.4 Key Developments
• 10.5 Intel Corporation
  • 10.5.1 Overview
  • 10.5.2 Financial Performance
  • 10.5.3 Product Outlook
  • 10.5.4 Key Developments
• 10.6 Nvidia Corporation
  • 10.6.1 Overview
  • 10.6.2 Financial Performance
  • 10.6.3 Product Outlook
  • 10.6.4 Key Developments
• 10.7 Oracle Corporation
  • 10.7.1 Overview
  • 10.7.2 Financial Performance
  • 10.7.3 Product Outlook
  • 10.7.4 Key Developments
• 10.8 Samsung
  • 10.8.1 Overview
  • 10.8.2 Financial Performance
  • 10.8.3 Product Outlook
  • 10.8.4 Key Developments
• 10.9 Lamasoft, Inc.
  • 10.9.1 Overview
  • 10.9.2 Financial Performance
  • 10.9.3 Product Outlook
  • 10.9.4 Key Developments

11 APPENDIX

• 11.1 Related Research