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Artificial Intelligence in Supply Chain Market Size

ID: MRFR/ICT/5766-HCR
100 Pages
Ankit Gupta
October 2025

AI in Supply Chain Market Research Report Information By Component (Software, Network, Hardware, FPGA, GPU, and ASIC), By End-users (Automotive, Retail, and Manufacturing), By Technology (Machine Learning and Natural Language Processing), And By Region (North America, Europe, Asia-Pacific, And Rest Of The World) –Market Forecast Till 2035

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Artificial Intelligence In Supply Chain Size

Artificial Intelligence in Supply Chain Market Growth Projections and Opportunities

Numerous market drivers that together determine the acceptance, expansion, and effect of AI technologies in improving supply chain operations are driving the artificial intelligence (AI) revolution in the supply chain industry. The need for operational agility and efficiency is one of the key market drivers pushing AI use in the supply chain. The need to quickly and accurately meet customer demands while adapting to changing market conditions has led to an increase in demand for AI-powered solutions that can automate processes, optimize inventory management, and boost overall supply chain efficiency. These needs are being driven by supply chains becoming more complex and globalized.

Furthermore, one of the main market factors propelling the use of AI is the abundance of data created throughout the supply chain ecosystem. AI technologies have the potential to analyze, interpret, and derive actionable insights from the massive volumes of data coming from sensors, enterprise systems, and external sources. This will help businesses make data-driven decisions, anticipate demand patterns, and optimize their supply chain operations with accuracy and foresight. The demand for improved transparency, visibility, and real-time monitoring in the supply chain is another strong market force propelling the use of AI technology. The need for AI technologies that can provide previously unheard-of levels of operational visibility and control is reflected in the growing number of businesses utilizing AI-powered solutions to track goods in transit, identify and mitigate potential bottlenecks or disruptions, and gain comprehensive insights into their supply chain operations.

Moreover, a key market element influencing the growth and use of AI in the supply chain is the convergence of AI with the Internet of Things (IoT). Businesses can now use real-time data for asset tracking, predictive maintenance, and intelligent decision-making thanks to the integration of AI with IoT sensors, devices, and connected systems. This is increasing demand for AI solutions that can coordinate intelligent, interconnected supply chain operations.

Artificial Intelligence in Supply Chain Market Size Graph
Author
Ankit Gupta
Senior Research Analyst

Ankit Gupta is an analyst in market research industry in ICT and SEMI industry. With post-graduation in "Telecom and Marketing Management" and graduation in "Electronics and Telecommunication" vertical he is well versed with recent development in ICT industry as a whole. Having worked on more than 150+ reports including consultation for fortune 500 companies such as Microsoft and Rio Tinto in identifying solutions with respect to business problems his opinions are inclined towards mixture of technical and managerial aspects.

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FAQs

What is the projected market valuation for AI in the Supply Chain Market by 2035?

The projected market valuation for AI in the Supply Chain Market is expected to reach 117.31 USD Billion by 2035.

What was the overall market valuation for AI in the Supply Chain Market in 2024?

The overall market valuation for AI in the Supply Chain Market was 51.35 USD Billion in 2024.

What is the expected CAGR for the AI in Supply Chain Market during the forecast period 2025 - 2035?

The expected CAGR for the AI in Supply Chain Market during the forecast period 2025 - 2035 is 7.8%.

Which companies are considered key players in the AI in Supply Chain Market?

Key players in the AI in Supply Chain Market include IBM, SAP, Oracle, Microsoft, Siemens, JDA Software, Blue Yonder, C3.ai, and Kinaxis.

What are the projected valuations for the software segment in the AI in Supply Chain Market by 2035?

The software segment is projected to grow from 20.0 USD Billion to 45.0 USD Billion by 2035.

How does the hardware segment's valuation change from 2024 to 2035?

The hardware segment's valuation is expected to increase from 8.0 USD Billion to 15.0 USD Billion by 2035.

Market Summary

As per MRFR analysis, the AI in Supply Chain Market Size was estimated at 51.35 USD Billion in 2024. The AI in Supply Chain industry is projected to grow from 55.36 USD Billion in 2025 to 117.31 USD Billion by 2035, exhibiting a compound annual growth rate (CAGR) of 7.8 during the forecast period 2025 - 2035.

Key Market Trends & Highlights

The AI in Supply Chain Market is experiencing robust growth driven by technological advancements and evolving consumer demands.

  • North America remains the largest market for AI in supply chain solutions, reflecting a strong adoption of advanced technologies.
  • The Asia-Pacific region is emerging as the fastest-growing area, fueled by increasing investments in AI and automation.
  • The retail segment continues to dominate the market, while the automotive sector is witnessing the most rapid growth in AI applications.
  • Key market drivers include enhanced demand forecasting and cost reduction through automation, which are pivotal in shaping supply chain strategies.

Market Size & Forecast

2024 Market Size 51.35 (USD Billion)
2035 Market Size 117.31 (USD Billion)
CAGR (2025 - 2035) 7.8%
Largest Regional Market Share in 2024 North America

Major Players

<p>IBM (US), SAP (DE), Oracle (US), Microsoft (US), Siemens (DE), JDA Software (US), Blue Yonder (US), C3.ai (US), Kinaxis (CA)</p>

Market Trends

The AI in Supply Chain Market is currently experiencing a transformative phase, driven by advancements in technology and the increasing need for efficiency. Organizations are increasingly adopting artificial intelligence to optimize logistics, enhance inventory management, and improve demand forecasting. This shift appears to be motivated by the desire to reduce operational costs and improve service levels. As companies integrate AI solutions, they are likely to witness enhanced decision-making capabilities and greater agility in responding to market fluctuations. Furthermore, the growing emphasis on sustainability may also influence the adoption of AI technologies, as businesses seek to minimize their environmental impact while maintaining profitability. In addition, the AI in Supply Chain Market seems to be characterized by a surge in collaboration between technology providers and supply chain stakeholders. This collaboration may lead to the development of innovative solutions tailored to specific industry needs. Moreover, the increasing availability of data and advancements in machine learning algorithms could further enhance the capabilities of AI systems. As organizations continue to explore the potential of AI, it is anticipated that the market will evolve, presenting new opportunities and challenges for stakeholders across the supply chain spectrum.

Enhanced Predictive Analytics

The integration of AI technologies into supply chain operations is likely to improve predictive analytics capabilities. This enhancement may allow organizations to anticipate demand fluctuations more accurately, thereby optimizing inventory levels and reducing waste.

Automation of Supply Chain Processes

AI is expected to drive the automation of various supply chain processes, from procurement to logistics. This trend could lead to increased efficiency and reduced human error, enabling companies to streamline operations and focus on strategic initiatives.

Sustainability Initiatives

The growing focus on sustainability within the AI in Supply Chain Market suggests that companies are increasingly leveraging AI to develop eco-friendly practices. This may involve optimizing routes for transportation or improving resource allocation to minimize environmental impact.

Artificial Intelligence in Supply Chain Market Market Drivers

Supply Chain Visibility

In the AI in Supply Chain Market, enhanced visibility across the supply chain is becoming a critical driver. AI technologies facilitate real-time tracking of goods and materials, enabling companies to monitor their supply chain operations more effectively. This visibility allows for quicker decision-making and improved risk management. For instance, organizations that implement AI solutions report a 30% reduction in supply chain disruptions. By leveraging AI for visibility, companies can identify bottlenecks, optimize routes, and enhance collaboration with suppliers and partners. This increased transparency not only improves operational efficiency but also fosters trust among stakeholders, which is essential in today's interconnected supply chain landscape.

Enhanced Demand Forecasting

The AI in Supply Chain Market is experiencing a surge in demand forecasting capabilities, driven by advanced machine learning algorithms. These algorithms analyze historical data, market trends, and consumer behavior to predict future demand with remarkable accuracy. According to recent estimates, companies utilizing AI-driven forecasting can reduce inventory costs by up to 20%. This enhanced forecasting ability allows businesses to optimize their supply chain operations, ensuring that products are available when needed while minimizing excess stock. As a result, organizations are increasingly investing in AI technologies to refine their demand planning processes, thereby improving overall efficiency and responsiveness in the supply chain.

Cost Reduction through Automation

Automation powered by AI is a pivotal driver in the AI in Supply Chain Market, as it significantly reduces operational costs. By automating repetitive tasks such as order processing, inventory management, and logistics planning, companies can streamline their operations and allocate resources more effectively. Research indicates that businesses adopting AI-driven automation can achieve cost savings of up to 25%. This reduction in costs is particularly beneficial in competitive markets where margins are tight. Furthermore, automation enhances accuracy and reduces human error, leading to improved service levels and customer satisfaction. As organizations seek to remain competitive, the integration of AI in automating supply chain processes is likely to accelerate.

Sustainability and Ethical Sourcing

Sustainability initiatives are becoming a key driver in the AI in Supply Chain Market, as companies strive to meet consumer demand for ethical sourcing and environmentally friendly practices. AI technologies facilitate the analysis of supply chain data to identify sustainable sourcing options and optimize resource usage. Organizations that implement AI-driven sustainability measures can reduce waste and improve their carbon footprint. Reports indicate that companies focusing on sustainability can enhance their brand reputation and customer loyalty, leading to increased market share. As consumers become more environmentally conscious, the integration of AI in promoting sustainable practices within the supply chain is likely to gain momentum.

Improved Supplier Relationship Management

The AI in Supply Chain Market is witnessing a transformation in supplier relationship management, driven by AI technologies. These tools enable companies to analyze supplier performance, assess risks, and identify opportunities for collaboration. By leveraging AI, organizations can enhance their negotiation strategies and foster stronger partnerships with suppliers. Data suggests that companies utilizing AI for supplier management experience a 15% improvement in supplier performance metrics. This improvement is crucial for maintaining a resilient supply chain, as strong supplier relationships can lead to better pricing, quality, and reliability. As businesses increasingly recognize the value of AI in managing supplier relationships, investment in these technologies is expected to grow.

Market Segment Insights

By Component: GPU (Largest) vs. Software (Fastest-Growing)

<p>In the AI in Supply Chain Market, the component segment is predominantly driven by GPUs, which have secured a significant market share. GPUs are increasingly being utilized for complex computations and data analysis, making them crucial for AI applications in supply chains. On the other hand, software solutions are rapidly gaining traction, representing the fastest-growing aspect of this segment, as companies adopt advanced AI-driven applications to enhance efficiency and decision-making.</p>

<p>GPU (Dominant) vs. Software (Emerging)</p>

<p>GPUs serve as the backbone of AI in Supply Chain operations owing to their unparalleled processing capabilities, significantly speeding up the data analysis and machine learning processes. Their established position is supported by strong demand for enhanced predictive analytics and real-time decision-making in supply chains. Conversely, software solutions, often termed as emerging, are revolutionizing this market by integrating AI technologies that optimize logistics, inventory management, and supplier relations. This segment is seeing exponential growth as organizations transition towards more automated and intelligent systems that foster agility and responsiveness in supply chain operations.</p>

By End-users: Retail (Largest) vs. Automotive (Fastest-Growing)

<p>The AI in Supply Chain Market is majorly driven by the retail sector, which holds a substantial market share due to its rapid integration of AI technologies for inventory management, customer demand forecasting, and supply chain optimization. Retailers utilize AI to enhance their operational efficiency and deliver personalized customer experiences, leading to its dominant position in the end-user segment. Conversely, the automotive industry is rapidly adopting AI solutions, driven by the need for advanced manufacturing processes, autonomous vehicles, and real-time supply chain analytics, making it a significant player in the market.</p>

<p>Retail (Dominant) vs. Automotive (Emerging)</p>

<p>The retail sector stands as the dominant force in the AI in Supply Chain Market, largely due to its adoption of AI for operational enhancements. Retailers leverage AI for predictive analytics, personalized marketing, and enhanced inventory management, which streamlines their supply chain processes. In contrast, the automotive industry is emerging as a key player, increasingly integrating AI to improve operational efficiency and support innovations like autonomous vehicles. The growing demand for smart manufacturing solutions and enhanced logistics capabilities positions automotive AI applications as a pivotal emerging trend, where manufacturers are focusing on AI for real-time data analysis and supply chain resilience.</p>

By Technology: Machine Learning (Largest) vs. Natural Language Processing (Fastest-Growing)

<p>In the AI in Supply Chain Market, Machine Learning dominates the technology segment due to its vast applications in predictive analytics and inventory optimization. It holds the largest market share as businesses increasingly rely on data-driven insights to enhance efficiency and reduce costs. Natural Language Processing (NLP), while smaller in market share, is rapidly gaining traction as organizations harness its capabilities for automating customer interactions and facilitating real-time decision-making in supply chains. The growth trends for these technologies reveal a dynamic landscape. Machine Learning continues to be the backbone of AI in supply chains, with many companies integrating it into their operations to improve forecasting accuracy. Conversely, NLP is emerging as a crucial component for enhancing communication and operational responsiveness, driven by the increasing demand for smarter automation tools that can understand and process human language effectively.</p>

<p>Technology: Machine Learning (Dominant) vs. Natural Language Processing (Emerging)</p>

<p>Machine Learning, as the dominant technology in the AI in Supply Chain Market, is characterized by its ability to analyze large datasets and generate actionable insights for supply chain optimization. Its applications extend from demand forecasting to predictive maintenance, allowing companies to make informed decisions that enhance operational efficiency. Companies investing in Machine Learning can leverage historical data to predict future trends, leading to more strategic resources allocation. On the other hand, Natural Language Processing (NLP) is an emerging technology that focuses on enabling machines to understand and respond to human language. As supply chains become increasingly complex, the demand for technologies that can interpret and analyze customer feedback, inquiries, and global communication has surged. NLP is instrumental in streamlining communication processes, automating customer service interactions, and enhancing real-time data analysis.</p>

Get more detailed insights about Artificial Intelligence (AI) in Supply Chain Market Research Report – Global Forecast till 2035

Regional Insights

North America : Innovation and Leadership Hub

North America is the largest market for AI in the supply chain, holding approximately 45% of the global market share. The region's growth is driven by rapid technological advancements, increased investment in AI technologies, and a strong focus on automation and efficiency. Regulatory support from government initiatives further catalyzes this growth, fostering an environment conducive to innovation and adoption of AI solutions. The United States leads the market, with significant contributions from Canada. Major players like IBM, Oracle, and Microsoft are headquartered here, driving competition and innovation. The presence of advanced infrastructure and a skilled workforce enhances the region's competitive landscape, making it a focal point for AI development in supply chains. Companies are increasingly leveraging AI to optimize logistics, reduce costs, and improve decision-making processes.

Europe : Regulatory Framework and Growth

Europe is the second-largest market for AI in the supply chain, accounting for approximately 30% of the global market share. The region's growth is propelled by stringent regulations aimed at enhancing supply chain transparency and sustainability. Initiatives like the European Green Deal and the Digital Single Market strategy are pivotal in driving demand for AI solutions that improve efficiency and reduce environmental impact. Germany and the United Kingdom are the leading countries in this sector, with a strong presence of key players such as SAP and Siemens. The competitive landscape is characterized by a mix of established firms and innovative startups, all striving to leverage AI for enhanced supply chain management. The European market is increasingly focused on integrating AI with IoT and blockchain technologies to create more resilient and efficient supply chains.

Asia-Pacific : Rapid Growth and Adoption

Asia-Pacific is witnessing rapid growth in the AI supply chain market, holding about 20% of the global market share. The region's expansion is driven by increasing investments in technology, a burgeoning e-commerce sector, and a growing emphasis on digital transformation across industries. Countries like China and India are at the forefront, supported by favorable government policies and initiatives aimed at enhancing technological capabilities. China is the largest market in the region, with significant contributions from India and Japan. The competitive landscape is vibrant, featuring both local and international players. Companies are increasingly adopting AI to streamline operations, enhance customer experiences, and improve supply chain visibility. The region's focus on innovation and technology adoption positions it as a key player in The AI in Supply Chain.

Middle East and Africa : Emerging Market Potential

The Middle East and Africa region is emerging as a potential market for AI in the supply chain, currently holding about 5% of the global market share. The growth is driven by increasing investments in technology and a rising demand for efficient supply chain solutions. Governments are recognizing the importance of digital transformation, leading to initiatives that support AI adoption in various sectors, including logistics and manufacturing. Countries like South Africa and the UAE are leading the charge, with a growing number of startups and established companies exploring AI applications in supply chains. The competitive landscape is evolving, with local firms partnering with global technology providers to enhance their capabilities. As the region continues to invest in infrastructure and technology, the potential for AI in supply chains is expected to expand significantly.

Key Players and Competitive Insights

Leading market players are investing heavily in research and development to expand their product lines, which will help the AI in Supply Chain market grow even more. Market participants are also undertaking various strategic activities to expand their footprint, with important market developments including new product launches, contractual agreements, mergers and acquisitions, higher investments, and collaboration with other organizations. To expand and survive in a more competitive and rising market climate, the AI in Supply Chain industry must offer cost-effective items.

Manufacturing locally to minimize operational costs is one of the key business tactics manufacturers use in the AI in Supply Chain industry to benefit clients and increase the market sector. The AI in Supply Chain industry has recently offered some of the most significant medical advantages. Major players in the AI in Supply Chain market, including Nvidia Corporation, IBM Corporation, Intel Corporation, Xilinx Inc., Samsung Electronics, Microsoft Corporation, Micron Technology, SAP SE, Oracle Corporation, Logility Inc., Amazon, LLamasoft and others are attempting to increase market demand by investing in research and development operations.

Nvidia Corporation NVIDIA pioneered accelerated computing to solve problems no one else could. Our work in artificial intelligence and the metaverse transforms the world's largest industries and profoundly impacts society. The metaverse, or 3D internet, promises a world where virtual collaboration is simple and industrial behemoths can reap the benefits of digital twins. NVIDIA OmniverseTM is a tool for creating and managing metaverse applications.

IBM Corporation, bring together all of the necessary technology and services, regardless of source, to assist clients in solving the most pressing business problems. Transformation is evolving from one-time project to an urgent, purpose-driven imperative. Modern businesses must move faster while also exhibiting greater empathy and openness. IBM Consulting is a new partner for modern business's new rules. We embrace an open way of working by bringing together a diverse set of voices and technologies. We work closely together, freely ideate, and quickly apply breakthrough innovations that exponentially impact how business is done.

We believe that open ecosystems, technologies, innovation, and cultures are critical to creating opportunities and charting the course for modern business and society.

Key Companies in the Artificial Intelligence in Supply Chain Market market include

Industry Developments

  • Q1 2024: IBM launches LogiGen AI, a generative AI solution for logistics and transportation IBM introduced LogiGen AI, a generative AI platform designed to optimize route planning, demand forecasting, and anomaly detection for logistics providers, aiming to enhance operational efficiency and supply chain agility.
  • Q2 2024: Sanofi deploys AI-driven supply chain management to mitigate €300 million in revenue risks Sanofi implemented advanced AI systems to manage its global supply chain, enabling the company to predict and avoid significant inventory risks and improve operational efficiency.
  • Q2 2024: AI-managed supply chains experience 47% more cyberattack attempts in 2024 The World Economic Forum highlighted a surge in cyberattack attempts targeting AI-powered supply chains, prompting companies to invest in advanced AI security solutions and risk mitigation strategies.
  • Q2 2024: DocShipper launches predictive logistics platform with 87% accuracy for shipping delay forecasts DocShipper unveiled a new AI-powered simulation platform that predicts shipping delays up to 9 days in advance, allowing clients to proactively implement mitigation strategies.
  • Q2 2024: IBM partners with Maersk to deploy generative AI for global supply chain optimization IBM and Maersk announced a strategic partnership to integrate generative AI into Maersk’s global logistics operations, focusing on network design optimization and autonomous planning.
  • Q2 2024: Sanofi appoints new Chief Digital Supply Chain Officer to lead AI transformation Sanofi named a new executive to oversee its digital supply chain initiatives, emphasizing the company’s commitment to AI-driven operational improvements.
  • Q2 2024: DHL opens new AI-powered logistics hub in Singapore DHL inaugurated a state-of-the-art logistics facility in Singapore featuring AI-driven warehouse automation and predictive analytics for supply chain management.
  • Q3 2024: Microsoft acquires supply chain AI startup ClearMetal Microsoft completed the acquisition of ClearMetal, a startup specializing in AI-powered supply chain visibility and predictive analytics, to bolster its enterprise cloud offerings.
  • Q3 2024: Amazon launches AI-powered digital twin platform for supply chain simulation Amazon introduced a new digital twin platform leveraging AI to simulate and optimize supply chain operations, enabling real-time scenario testing and autonomous implementation.
  • Q3 2024: FourKites raises $80M to expand AI-driven supply chain visibility solutions Supply chain technology company FourKites secured $80 million in funding to accelerate development of its AI-powered visibility and predictive analytics platform.
  • Q4 2024: Siemens and SAP announce joint AI initiative for supply chain resilience Siemens and SAP launched a collaborative initiative to develop AI-powered tools for enhancing supply chain resilience and real-time risk management.
  • Q1 2025: Flexport wins $100M contract to deploy AI logistics platform for US government supply chains Flexport secured a major contract to implement its AI-driven logistics platform across multiple US government supply chains, focusing on predictive analytics and operational efficiency.

Future Outlook

Artificial Intelligence in Supply Chain Market Future Outlook

<p>The AI in Supply Chain Market is projected to grow at a 7.8% CAGR from 2024 to 2035, driven by automation, data analytics, and enhanced decision-making capabilities.</p>

New opportunities lie in:

  • <p>Integration of AI-driven predictive analytics for inventory management.</p>
  • <p>Development of autonomous delivery systems for last-mile logistics.</p>
  • <p>Implementation of AI-based demand forecasting tools for supply chain optimization.</p>

<p>By 2035, the market is expected to be robust, characterized by advanced AI applications and increased operational efficiencies.</p>

Market Segmentation

Artificial Intelligence in Supply Chain Market Component Outlook

  • Software
  • Network
  • Hardware
  • FPGA
  • GPU
  • ASIC

Artificial Intelligence in Supply Chain Market End-users Outlook

  • Automotive
  • Retail
  • Manufacturing

Artificial Intelligence in Supply Chain Market Technology Outlook

  • Machine Learning
  • Natural Language Processing

Report Scope

MARKET SIZE 202451.35(USD Billion)
MARKET SIZE 202555.36(USD Billion)
MARKET SIZE 2035117.31(USD Billion)
COMPOUND ANNUAL GROWTH RATE (CAGR)7.8% (2024 - 2035)
REPORT COVERAGERevenue Forecast, Competitive Landscape, Growth Factors, and Trends
BASE YEAR2024
Market Forecast Period2025 - 2035
Historical Data2019 - 2024
Market Forecast UnitsUSD Billion
Key Companies ProfiledMarket analysis in progress
Segments CoveredMarket segmentation analysis in progress
Key Market OpportunitiesIntegration of advanced analytics and machine learning enhances efficiency in the AI in Supply Chain Market.
Key Market DynamicsRising integration of artificial intelligence enhances supply chain efficiency and responsiveness amid evolving consumer demands.
Countries CoveredNorth America, Europe, APAC, South America, MEA

FAQs

What is the projected market valuation for AI in the Supply Chain Market by 2035?

The projected market valuation for AI in the Supply Chain Market is expected to reach 117.31 USD Billion by 2035.

What was the overall market valuation for AI in the Supply Chain Market in 2024?

The overall market valuation for AI in the Supply Chain Market was 51.35 USD Billion in 2024.

What is the expected CAGR for the AI in Supply Chain Market during the forecast period 2025 - 2035?

The expected CAGR for the AI in Supply Chain Market during the forecast period 2025 - 2035 is 7.8%.

Which companies are considered key players in the AI in Supply Chain Market?

Key players in the AI in Supply Chain Market include IBM, SAP, Oracle, Microsoft, Siemens, JDA Software, Blue Yonder, C3.ai, and Kinaxis.

What are the projected valuations for the software segment in the AI in Supply Chain Market by 2035?

The software segment is projected to grow from 20.0 USD Billion to 45.0 USD Billion by 2035.

How does the hardware segment's valuation change from 2024 to 2035?

The hardware segment's valuation is expected to increase from 8.0 USD Billion to 15.0 USD Billion by 2035.

  1. Executive Summary
  2. Scope of the Report
    1. Market Definition
    2. Scope of the Study
    3. Research Objectives
    4. Markets Structure
  3. Research Methodology
  4. Market Dynamics
    1. Market Drivers
      1. Increasing market growth of E-commerce
      2. Increasing growth in big data technology
      3. High demand for advanced solutions for transparency in supply chain process
    2. Market Restraints
      1. Lack of technical expertise
    3. Market Opportunities
      1. Increasing adoption of cloud-based software modules by supply chain industry
      2. Rising trend of deploying automation solutions by industries into their operations
      3. Growth in industry 4.0
    4. Market Challenges
      1. Data privacy
      2. Lack of connected systems in sectors such as retail and logistics
    5. Value Chain analysis
    6. Porter’s Five Forces Analysis
      1. Threat of New Entrants
      2. Bargaining Power of Buyers
      3. Threat of Substitutes
      4. Segment Rivalry
      5. Bargaining Power of Suppliers
  5. Market Alerts
    1. Impact Analysis of Emerging Technologies
    2. Use Cases
      1. Chatbots
      2. Autonomous Vehicles
      3. Supplier Relationship Management
    3. Government/Industry Norms and Regulations
  6. Artificial Intelligence (AI) in Supply Chain Market by Component
    1. Introduction
    2. Hardware
      1. Market Estimates & Forecast, 2023-2030
      2. Market Estimates & Forecast by Region, 2023-2030
      3. Processors
      4. Memory
      5. Network
  7. Artificial Intelligence (AI) in Supply Chain Market by Technology
    1. Introduction
    2. Machine Learning
      1. Market Estimates & Forecast, 2023-2030
      2. Market Estimates & Forecast by Region, 2023-2030
    3. Natural Language processing (NLP)
      1. Market Estimates & Forecast, 2023-2030
      2. Market Estimates & Forecast by Region, 2023-2030
    4. Context-aware computing
      1. Market Estimates & Forecast, 2023-2030
      2. Market Estimates & Forecast by Region, 2023-2030
    5. Computer Vision
      1. Market Estimates & Forecast, 2023-2030
      2. Market Estimates & Forecast by Region, 2023-2030
  8. Artificial Intelligence (AI) in Supply Chain Market by Deployment
    1. Introduction
    2. On-premise
      1. Market Estimates & Forecast, 2023-2030
      2. Market Estimates & Forecast by Region, 2023-2030
    3. On-cloud
      1. Market Estimates & Forecast, 2023-2030
      2. Market Estimates & Forecast by Region, 2023-2030
    4. Hybrid
      1. Market Estimates & Forecast, 2023-2030
      2. Market Estimates & Forecast by Region, 2023-2030
  9. Artificial Intelligence (AI) in Supply Chain Market by Applications
    1. Introduction
    2. Fleet management
      1. Market Estimates & Forecast, 2023-2030
      2. Market Estimates & Forecast by Region, 2023-2030
    3. Warehouse management
      1. Market Estimates & Forecast, 2023-2030
      2. Market Estimates & Forecast by Region, 2023-2030
    4. Supply chain planning
      1. Market Estimates & Forecast, 2023-2030
      2. Market Estimates & Forecast by Region, 2023-2030
    5. Logistics & shipping
      1. Market Estimates & Forecast, 2023-2030
      2. Market Estimates & Forecast by Region, 2023-2030
    6. Supplier relationship management
      1. Market Estimates & Forecast, 2023-2030
      2. Market Estimates & Forecast by Region, 2023-2030
    7. Risk management
      1. Market Estimates & Forecast, 2023-2030
      2. Market Estimates & Forecast by Region, 2023-2030
    8. Others
      1. Market Estimates & Forecast, 2023-2030
      2. Market Estimates & Forecast by Region, 2023-2030
  10. Artificial Intelligence (AI) in Supply Chain Market by Vertical
    1. Introduction
    2. Aerospace
      1. Market Estimates & Forecast, 2023-2030
      2. Market Estimates & Forecast by Region, 2023-2030
    3. Automotive
      1. Market Estimates & Forecast, 2023-2030
      2. Market Estimates & Forecast by Region, 2023-2030
    4. Retail
      1. Market Estimates & Forecast, 2023-2030
      2. Market Estimates & Forecast by Region, 2023-2030
    5. Manufacturing
      1. Market Estimates & Forecast, 2023-2030
      2. Market Estimates & Forecast by Region, 2023-2030
    6. Food & beverage
      1. Market Estimates & Forecast, 2023-2030
      2. Market Estimates & Forecast by Region, 2023-2030
    7. Consumer electronics
      1. Market Estimates & Forecast, 2023-2030
      2. Market Estimates & Forecast by Region, 2023-2030
    8. Others
      1. Market Estimates & Forecast, 2023-2030
      2. Market Estimates & Forecast by Region, 2023-2030
  11. Artificial Intelligence (AI) in Supply Chain Market by Region
    1. Introduction
    2. North America
      1. Market Estimates & Forecast by Country, 2023-2030
      2. Market Estimates & Forecast by Component, 2023-2030
      3. Market Estimates & Forecast by Technology, 2023-2030
      4. Market Estimates & Forecast by Deployment, 2023-2030
      5. Market Estimates & Forecast by Applications, 2023-2030
      6. Market Estimates & Forecast by End-Users, 2023-2030
      7. US
      8. Mexico
      9. Canada
    3. Europe
      1. Market Estimates & Forecast by Country, 2023-2030
      2. Market Estimates & Forecast by Component, 2023-2030
      3. Market Estimates & Forecast by Technology, 2023-2030
      4. Market Estimates & Forecast by Deployment, 2023-2030
      5. Market Estimates & Forecast by Applications, 2023-2030
      6. Market Estimates & Forecast by End-Users, 2023-2030
      7. Germany
      8. France
      9. Italy
      10. Spain
      11. UK
      12. Rest of Europe
    4. Asia-Pacific
      1. Market Estimates & Forecast by Country, 2023-2030
      2. Market Estimates & Forecast by Component, 2023-2030
      3. Market Estimates & Forecast by Technology, 2023-2030
      4. Market Estimates & Forecast by Deployment, 2023-2030
      5. Market Estimates & Forecast by Applications, 2023-2030
      6. Market Estimates & Forecast by End-Users, 2023-2030
      7. China
      8. India
      9. Japan
      10. Singapore
      11. Rest of Asia-Pacific
    5. Rest of the World
      1. Market Estimates & Forecast by Country, 2023-2030
      2. Market Estimates & Forecast by Component, 2023-2030
      3. Market Estimates & Forecast by Technology, 2023-2030
      4. Market Estimates & Forecast by Deployment, 2023-2030
      5. Market Estimates & Forecast by Applications, 2023-2030
      6. Market Estimates & Forecast by End-Users, 2023-2030
      7. Middle East & Africa
      8. South America
  12. Competitive Landscape
    1. Key Players Market Share Analysis, 2020/2020 (%)
    2. Competitive Benchmarking
    3. Key Developments Analysis, 2020/2020
      1. Mergers & Acquisition
      2. Product Developments
      3. Business Expansion
      4. Partnerships & Collaborations
      5. Agreements
  13. Company Profiles
    1. Nvidia Corporation
      1. Company Overview
      2. Product/Business Segment Overview
      3. Financial Updates
      4. Key Developments
      5. SWOT Analysis
      6. Key Strategy
    2. IBM corporation
      1. Company Overview
      2. Product/Business Segment Overview
      3. Financial Updates
      4. Key Developments
      5. SWOT Analysis
      6. Key Strategy
    3. Intel Corporation
      1. Company Overview
      2. Product/Business Segment Overview
      3. Financial Updates
      4. Key Developments
      5. SWOT Analysis
      6. Key Strategy
    4. Xilinx, Inc.
      1. Company Overview
      2. Product/Business Segment Overview
      3. Financial Updates
      4. Key Developments
      5. SWOT Analysis
      6. Key Strategy
    5. Samsung Electronics
      1. Company Overview
      2. Product/Business Segment Overview
      3. Financial Updates
      4. Key Developments
      5. SWOT Analysis
      6. Key Strategy
    6. Microsoft Corporation
      1. Company Overview
      2. Product/Business Segment Overview
      3. Financial Updates
      4. Key Developments
      5. SWOT Analysis
      6. Key Strategy
    7. Micron Technology
      1. Company Overview
      2. Product/Business Segment Overview
      3. Financial Updates
      4. Key Developments
      5. SWOT Analysis
      6. Key Strategy
    8. SAP SE
      1. Company Overview
      2. Product/Business Segment Overview
      3. Financial Updates
      4. Key Developments
      5. SWOT Analysis
      6. Key Strategy
    9. Oracle Corporation
      1. Company Overview
      2. Product/Business Segment Overview
      3. Financial Updates
      4. Key Developments
      5. SWOT Analysis
      6. Key Strategy
    10. Logility, Inc.
      1. Company Overview
      2. Product/Business Segment Overview
      3. Financial Updates
      4. Key Developments
      5. SWOT Analysis
      6. Key Strategy
    11. Amazon
      1. Company Overview
      2. Product/Business Segment Overview
      3. Financial Updates
      4. Key Developments
      5. SWOT Analysis
      6. Key Strategy
    12. LLamasoft, Inc
      1. Company Overview
      2. Product/Business Segment Overview
      3. Financial Updates
      4. Key Developments
      5. SWOT Analysis
      6. Key Strategy
  14. Conclusion/Recommendations
  15. LIST OF TABLES
  16. Artificial Intelligence (AI) in Supply Chain Market, by Region, 2023-2030
  17. North America: Artificial Intelligence (AI) in Supply Chain Market, by Country, 2023-2030
  18. Europe: Artificial Intelligence (AI) in Supply Chain Market, by Country, 2023-2030
  19. Asia-Pacific: Artificial Intelligence (AI) in Supply Chain Market, by Country, 2023-2030
  20. Rest of the World: Artificial Intelligence (AI) in Supply Chain Market, by Country, 2023-2030
  21. North America: Casino Management System Component Market, by Country, 2023-2030
  22. Europe: Casino Management System Component Market, by Country, 2023-2030
  23. Asia-Pacific: Casino Management System Component Market, by Country, 2023-2030
  24. Rest of the World: Casino Management System Component Market, by Country, 2023-2030
  25. Global Casino Management System Component Market, by Region, 2023-2030
  26. North America: Casino Management System Component Market, by Country, 2023-2030
  27. Europe: Casino Management System Component Market, by Country, 2023-2030
  28. Asia-Pacific: Casino Management System Component Market, by Country, 2023-2030
  29. Rest of the World: Casino Management System Component Market, by Country, 2023-2030
  30. Global Casino Management System Applications Market, by Region, 2023-2030
  31. North America: Casino Management System Applications Market, by Country, 2023-2030
  32. Europe: Casino Management System Applications Market, by Country, 2023-2030
  33. Asia-Pacific: Casino Management System Applications Market, by Country, 2023-2030
  34. Rest of the World: Casino Management System Applications Market, by Country, 2023-2030
  35. LIST OF FIGURES
  36. Global Artificial Intelligence (AI) in Supply Chain Market Segmentation
  37. Forecast Methodology
  38. Porter’s Five Forces Analysis of Global Artificial Intelligence (AI) in Supply Chain Market
  39. Value Chain/supply chain of Global Artificial Intelligence (AI) in Supply Chain Market
  40. Share of Global Artificial Intelligence (AI) in Supply Chain Market in 2020, by Country (in %)
  41. Global Artificial Intelligence (AI) in Supply Chain Market, 2023-2030
  42. Sub-segments of Component
  43. Global Artificial Intelligence (AI) in Supply Chain Market Size, by Component, 2020
  44. Share of Global Artificial Intelligence (AI) in Supply Chain Market, by Component, 2020 to 2027
  45. Global Artificial Intelligence (AI) in Supply Chain Market Size, by Component, 2020
  46. Share of Global Artificial Intelligence (AI) in Supply Chain Market, by Component, 2020 to 2027
  47. Global Artificial Intelligence (AI) in Supply Chain Market Size, by Applications, 2020
  48. Share of Global Artificial Intelligence (AI) in Supply Chain Market, by Applications, 2020 to 2027
    1. '

AI in Supply Chain Market Segmentation

AI in Supply Chain Component Outlook (USD Billion, 2019-2030)

Software

Network

Hardware

FPGA

GPU

ASIC

AI in Supply Chain End-users Outlook (USD Billion, 2019-2030)

Automotive

Retail

Manufacturing

AI in Supply Chain Technology Outlook (USD Billion, 2019-2030)

Machine Learning

Natural Language Processing

AI in Supply Chain Regional Outlook (USD Billion, 2019-2030)

North America Outlook (USD Billion, 2019-2030)

North America AI in Supply Chain by Component

Software

Network

Hardware

FPGA

GPU

ASIC

North America AI in Supply Chain by End-users

Automotive

Retail

Manufacturing

North America AI in Supply Chain by Technology

Machine Learning

Natural Language Processing

US Outlook (USD Billion, 2019-2030)

US AI in Supply Chain by Component

Software

Network

Hardware

FPGA

GPU

ASIC

US AI in Supply Chain by End-users

Automotive

Retail

Manufacturing

US AI in Supply Chain by Technology

Machine Learning

Natural Language Processing

CANADA Outlook (USD Billion, 2019-2030)

CANADA AI in Supply Chain by Component

Software

Network

Hardware

FPGA

GPU

ASIC

CANADA AI in Supply Chain by End-users

Automotive

Retail

Manufacturing

CANADA AI in Supply Chain by Technology

Machine Learning

Natural Language Processing

Europe Outlook (USD Billion, 2019-2030)

Europe AI in Supply Chain by Component

Software

Network

Hardware

FPGA

GPU

ASIC

Europe AI in Supply Chain by End-users

Automotive

Retail

Manufacturing

Europe AI in Supply Chain by Technology

Machine Learning

Natural Language Processing

Germany Outlook (USD Billion, 2019-2030)

Germany AI in Supply Chain by Component

Software

Network

Hardware

FPGA

GPU

ASIC

Germany AI in Supply Chain by End-users

Automotive

Retail

Manufacturing

Germany AI in Supply Chain by Technology

Machine Learning

Natural Language Processing

France Outlook (USD Billion, 2019-2030)

France AI in Supply Chain by Component

Software

Network

Hardware

FPGA

GPU

ASIC

France AI in Supply Chain by End-users

Automotive

Retail

Manufacturing

France AI in Supply Chain by Technology

Machine Learning

Natural Language Processing

UK Outlook (USD Billion, 2019-2030)

UK AI in Supply Chain by Component

Software

Network

Hardware

FPGA

GPU

ASIC

UK AI in Supply Chain by End-users

Automotive

Retail

Manufacturing

UK AI in Supply Chain by Technology

Machine Learning

Natural Language Processing

ITALY Outlook (USD Billion, 2019-2030)

ITALY AI in Supply Chain by Component

Software

Network

Hardware

FPGA

GPU

ASIC

ITALY AI in Supply Chain by End-users

Automotive

Retail

Manufacturing

ITALY AI in Supply Chain by Technology

Machine Learning

Natural Language Processing

SPAIN Outlook (USD Billion, 2019-2030)

Spain AI in Supply Chain by Component

Software

Network

Hardware

FPGA

GPU

ASIC

Spain AI in Supply Chain by End-users

Automotive

Retail

Manufacturing

Spain AI in Supply Chain by Technology

Machine Learning

Natural Language Processing

Rest of Europe Outlook (USD Billion, 2019-2030)

Rest of Europe AI in Supply Chain by Component

Software

Network

Hardware

FPGA

GPU

ASIC

REST OF EUROPE AI in Supply Chain by End-users

Automotive

Retail

Manufacturing

REST OF EUROPE AI in Supply Chain by Technology

Machine Learning

Natural Language Processing

Asia-Pacific Outlook (USD Billion, 2019-2030)

Asia-Pacific AI in Supply Chain by Component

Software

Network

Hardware

FPGA

GPU

ASIC

Asia-Pacific AI in Supply Chain by End-users

Automotive

Retail

Manufacturing

Asia-Pacific AI in Supply Chain by Technology

Machine Learning

Natural Language Processing

China Outlook (USD Billion, 2019-2030)

China AI in Supply Chain by Component

Software

Network

Hardware

FPGA

GPU

ASIC

China AI in Supply Chain by End-users

Automotive

Retail

Manufacturing

China AI in Supply Chain by Technology

Machine Learning

Natural Language Processing

Japan Outlook (USD Billion, 2019-2030)

Japan AI in Supply Chain by Component

Software

Network

Hardware

FPGA

GPU

ASIC

Japan AI in Supply Chain by End-users

Automotive

Retail

Manufacturing

Japan AI in Supply Chain by Technology

Machine Learning

Natural Language Processing

India Outlook (USD Billion, 2019-2030)

India AI in Supply Chain by Component

Software

Network

Hardware

FPGA

GPU

ASIC

India AI in Supply Chain by End-users

Automotive

Retail

Manufacturing

India AI in Supply Chain by Technology

Machine Learning

Natural Language Processing

Australia Outlook (USD Billion, 2019-2030)

Australia AI in Supply Chain by Component

Software

Network

Hardware

FPGA

GPU

ASIC

Australia AI in Supply Chain by End-users

Automotive

Retail

Manufacturing

Australia AI in Supply Chain by Technology

Machine Learning

Natural Language Processing

Rest of Asia-Pacific Outlook (USD Billion, 2019-2030)

Rest of Asia-Pacific AI in Supply Chain by Component

Software

Network

Hardware

FPGA

GPU

ASIC

Rest of Asia-Pacific AI in Supply Chain by End-users

Automotive

Retail

Manufacturing

Rest of Asia-Pacific AI in Supply Chain by Technology

Machine Learning

Natural Language Processing

Rest of the World Outlook (USD Billion, 2019-2030)

Rest of the World AI in Supply Chain by Component

Software

Network

Hardware

FPGA

GPU

ASIC

Rest of the World AI in Supply Chain by End-users

Automotive

Retail

Manufacturing

Rest of the World AI in Supply Chain by Technology

Machine Learning

Natural Language Processing

Middle East Outlook (USD Billion, 2019-2030)

Middle East AI in Supply Chain by Component

Software

Network

Hardware

FPGA

GPU

ASIC

Middle East AI in Supply Chain by End-users

Automotive

Retail

Manufacturing

Middle East AI in Supply Chain by Technology

Machine Learning

Natural Language Processing

Africa Outlook (USD Billion, 2019-2030)

Africa AI in Supply Chain by Component

Software

Network

Hardware

FPGA

GPU

ASIC

Africa AI in Supply Chain by End-users

Automotive

Retail

Manufacturing

Africa AI in Supply Chain by Technology

Machine Learning

Natural Language Processing

Latin America Outlook (USD Billion, 2019-2030)

Latin America AI in Supply Chain by Component

Software

Network

Hardware

FPGA

GPU

ASIC

Latin America AI in Supply Chain by End-users

Automotive

Retail

Manufacturing

Latin America AI in Supply Chain by Technology

Machine Learning

Natural Language Processing

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