AI in Supply Chain Market Size, Share, and Industry Analysis, By Component (Software and Services), By Deployment (On-premises and Cloud), By Application (Inventory Management, Warehouse Management, Supply Chain Visibility, Planning & Logistics, and Others), By Industry (Retail & E-commerce, Manufacturing, Automotive, Healthcare, and Others), and Regional Forecast till 2034

The global AI in supply chain market was valued at ~USD 10.50 billion in 2025. The market is projected to reach ~USD 143.50 billion by 2034, exhibiting a CAGR of 33.5% - 34.0% during the forecast period (2026-2034). The market is witnessing moderate growth, driven by the demand for real-time visibility into the supply chain. The need for planning using predictive models is expanding rapidly, leading to an increase in demand for the use of AI in predicting consumer demand, identifying disruptions, optimizing inventory levels, and improving decision-making throughout complex global supply chains.

Additionally, businesses are increasingly using automation in their logistics, procurement, and warehouse operations, speeding up the deployment of AI in these functions. The adoption is aimed at reducing operational costs, improving the efficiency of delivering products, and reducing human error.

Impact of Generative AI 

Generative AI is positively impacting the AI in supply chain market by moving AI use cases from predictive analytics to decision-support and autonomous planning workflows. Generative AI allows supply chain teams to ask open-ended/natural language questions, produce different Demand/Inventory scenarios, summarize supplier risk and recommend corrective actions, thus reducing manual effort associated with planning, procurement, logistics, and warehousing. For instance,

• In August 2025, Microsoft also highlighted Copilot and AI innovation in Dynamics 365 Supply Chain Management, showing how generative AI is being embedded into enterprise supply chain systems to improve productivity and operational decision-making.
• In June 2024, Kinaxis launched Maestro, an AI-infused supply chain orchestration platform designed to help teams make faster and smarter supply chain decisions, supporting the shift toward AI-led supply chain planning.

AI in Supply Chain Market Driver

Rising Demand for Accurate Demand Forecasting to Drive Market Growth

The growth of the market may be the result of the rising demand for more accurate demand forecasting as organizations will require improved visibility on customer demand, seasonal trends, inventory movements and interruptions in supply. Companies can use AI-based forecasting tools to examine historical sales, current market signals from customers, promotions, weather patterns and suppliers' information to reduce the risk of out of stock items by avoiding excess stock and optimizing their production planning processes.

According to Oracle, the use of AI-powered forecasting within the supply chain management (SCM) business functions will deliver a 20-50% reduction in the number of forecasting errors and up to a 65% decrease in instances of products being out of stock. This makes AI a significant driver of product adoption among retailers, manufacturers, and logistics-based enterprises. 

• In June 2025, Amazon announced new AI-powered supply chain innovations, including an AI demand forecasting model used to improve inventory placement and delivery operations, showing how large enterprises are applying AI to make supply chains more predictive and responsive.

AI in Supply Chain Market Restraint

High Implementation and Integration Costs May Hinder Market Growth

The high implementation and integration costs are barriers to the growth of the market. Organizations should invest in multiple resources (software, cloud infrastructure, data integration, cybersecurity, skilled personnel, and customized systems) to produce measurable value from an AI initiative. Additionally, many firms have ERP, procurement, warehouse, logistics, and supplier systems that are fragmented, which means deploying AI is costly and technically challenging. For instance,

• In January 2024, Oracle highlighted that implementing AI across supply chain operations can be difficult and expensive, as production deployments require powerful computing infrastructure and integration with sensors, devices, and existing enterprise systems.

This cost burden may result in delays with the use of AI within small- and medium-sized enterprises and organizations with outdated supply chain systems. This is specifically where they need to update their data and integrate the updated data before the AI models will be able to provide accurate recommendations.

AI in Supply Chain Market Opportunity

Increasing Demand for AI in Supply Chain from SMEs and Emerging Markets Aids the Market Growth

SMEs and developing economies continue to create strong opportunities for market players as enterprises move toward automated versus manual planning techniques, along with spreadsheet-based inventory systems to cloud-based AI tools that include conducting demand forecasts, achieving route optimization, gaining visibility into procurement activities, and managing suppliers’ risk. With SMEs making up 90% of businesses globally and comprising over 50% of total employment worldwide, they represent an enormous, largely unimproved market and will represent the largest market available for cost-effective AI-powered supply chain solutions in the coming years, particularly in developing nations. For instance,

• In September 2025, India-based Enmovil, an AI-driven supply chain planning and visibility startup, raised around USD 6 million in Series A funding to expand its AI-based supply chain intelligence platform for manufacturing companies. This highlights the rising investor and enterprise interest in emerging-market supply chain AI adoption.

Segmentation

Key Insights

The report covers the following key insights:

• Micro Macro Economic Indicators
• Drivers, Restraints, Trends, and Opportunities
• Business Strategies Adopted by the Key Players
• Impact of Generative AI on the Global AI in Supply Chain Market
• Consolidated SWOT Analysis of Key Players

Analysis by Component

By component, the market is divided into software and services.

The software segment captured the largest share in the market for the purchase of artificial intelligence-enabled supply chains. This is primarily due to their use of various types of platforms (e.g., demand forecasting, inventory optimization, transportation planning, procurement intelligence, warehouse management, and real-time visibility) that help businesses develop and manage their supply chains. 

• In May 2025, SAP announced AI-powered supply chain innovations under its network-centric supply chain management strategy, including SAP Business AI and Joule capabilities across supply chain planning and operations, highlighting how leading vendors are strengthening software-led AI adoption in the market.

Analysis by Deployment

By deployment, the market is bifurcated into on-premises and cloud.

The cloud deployment segment holds the largest share of the AI in supply chain market. As businesses increasingly utilize cloud-based solutions for deploying AI-supported supply chain solutions for faster delivery, more efficient data processing, real-time collaboration capabilities with suppliers, warehouses, logistics providers, and ERP platforms, and providing the ease of integration between these stakeholders within a supply chain network.

• In September 2025, Amazon Web Services (AWS) introduced the AWS Well-Architected Supply Chain Lens to help organizations design scalable, secure, and resilient cloud-based supply chain architectures. The framework supports cloud-native supply chain use cases such as planning and operations, procurement automation, warehouse optimization, and transportation visibility.

Analysis by Application

By application, the market is classified into inventory management, warehouse management, supply chain visibility, planning & logistics, and others (risk management).

The supply chain visibility segment captured the largest share of the AI in supply chain market. Companies have started concentrating on using AI tools to enable them to track shipments, inventories, suppliers, and demand changes, and assess potential disruptions in their global, complex supply chains, driving segment growth. 

• In April 2025, project44 and Lobster announced a strategic partnership to strengthen real-time, end-to-end supply chain visibility and execution transparency, supporting the growing enterprise focus on AI-enabled visibility platforms for faster risk detection and operational decision-making.

Analysis by Industry

By industry, the market is categorized into retail & e-commerce, manufacturing, automotive, healthcare, and others (food & beverages).

The automotive segment accounts for the largest share of the market. This is owing to the dependence placed on AI-based supply chain solutions by both the manufacturing industries and their associated tier one suppliers. Automakers are using AI solutions to assist with effectively managing complex multi-level supplier networks, including Ti50 suppliers, as well as concerning the supply of semiconductors/battery components, production logistics, inventory planning, and demand fluctuations occurring across global manufacturing plants.

• In July 2025, BMW Group and SAP announced the standardization of BMW’s production logistics using SAP S/4HANA, SAP Extended Warehouse Management, and SAP Transportation Management to improve efficiency, transparency, and AI readiness. Such developments are likely to support the automotive sector’s strong adoption of AI-ready supply chain platforms.

AI Maturity across Industries, 2025

• As per a survey by ServiceNow, Inc., the bar graph indicates that heavy manufacturing recorded the highest concentration of AI pacesetters among the selected industries at 21%, followed by automotive at 17% and healthcare providers at 16%, indicating comparatively stronger progress in integrating AI into enterprise workflows. Consumer goods and retail accounted for 15% and 14%, respectively, highlighting significant scope for further AI integration across demand planning, inventory management, logistics, and other supply chain processes.

Regional Analysis

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In terms of geography, the global market is segmented into North America, Europe, Asia Pacific, South America, and the Middle East & Africa.

North America accounted for the largest share of the global AI in supply chain market in 2025. This is owing to the strong presence of dominant providers of artificial intelligence (AI), cloud, enterprise resource planning (ERP), and supply chain software. Further, the rapid enterprise adoption of artificial intelligence planning, logistics visibility, warehouse automation and supplier risk management solutions in Canada and the U.S. has boosted the overall sales in North America. For instance,

• In February 2026, Oracle launched new AI agents within Oracle Fusion Cloud Applications to automate processes across supply-chain planning, procurement, manufacturing, inventory management, and logistics.

The European region depicts the second largest demand for AI in supply chain, as companies across automotive, manufacturing, retail & logistics are adopting the technology in their supply chain operations for demand planning, supplier risk monitoring, inventory optimization, and end-to-end visibility. The ongoing digitalization and green supply chain initiatives in many countries within Europe support this trend. As evidenced by the current EIB Investment Survey; approximately 37% of EU based firms have implemented generative AI technologies versus the US at approximately 36%. Through supportive regulatory and industrial policy frameworks including the EU AI Act and the broader European Union AI strategy, enterprises are encouraged to adopt trustworthy AI systems through supply chain operations.

The AI in supply chain market in the Asia Pacific is expected to grow at the highest CAGR during the forecast period. This is owing to the rapid adoption of digital technology in countries such as China, India, Japan, South Korea, and Southeast Asia by manufacturers, e-commerce companies, and logistics firms. These organizations will use AI for demand forecasting, optimization of inventory, planning of routes, automating warehouses, and providing real-time visibility into their supply chains. 

• In June 2025, DHL’s E-Commerce Trends Report 2025 stated that 81% of shoppers in Asia Pacific want retailers to offer AI-powered shopping features.

Moreover, the AI in supply chain market in China is growing, owing to the country’s manufacturing, e-commerce, automotive, and logistics industry bases, as more firms continue to incorporate AI into their operational practices. These firms are utilizing AI for various purposes, including demand forecasting, planning for smart factories, automating warehouses, optimizing inventory, and improving transportation efficiency. 

• In May 2025, China introduced an action plan to develop digital and intelligent supply chains across agriculture, manufacturing, wholesale, retail, and logistics, supporting wider AI adoption in supply chain operations.

Key Players Covered

The global AI in supply chain market is fragmented, with a large number of groups and standalone providers. In the U.S., the top 5 players account for around 21% of the market.

The report includes the profiles of the following key players:

• SAP SE (Germany)
• Microsoft Corporation (U.S.)
• IBM Corporation (U.S.)
• Oracle Corporation (U.S.)
• Blue Yonder Group, Inc. (U.S.)
• Kinaxis Inc. (Canada)
• o9 Solutions, Inc. (U.S.)
• Coupa Software Inc. (U.S.)
• Manhattan Associates, Inc. (U.S.)
• Infor Inc. (U.S.)

Key Industry Developments

• October 2025: Kinaxis launched Maestro Agents, AI-powered digital co-workers embedded in Kinaxis Maestro to help planners move faster from issue detection to corrective action. The launch supports the wider adoption of agentic AI for supply chain orchestration, disruption response, and decision intelligence.
• September 2025: o9 Solutions partnered with Databricks to accelerate time-to-value for supply chain planning by connecting Databricks’ Data Intelligence Platform with o9’s Digital Brain platform. The partnership helps enterprises convert large volumes of supply chain data into faster planning and decision-making capabilities.