According to our (Global Info Research) latest study, the global Enterprise Supply Chain AI Agent market size was valued at US$ 1631 million in 2025 and is forecast to a readjusted size of US$ 12518 million by 2032 with a CAGR of 27.3% during review period.
An enterprise supply chain AI agent is an intelligent software system built upon technologies such as large language models, machine learning, knowledge graphs, operations research optimization, and process automation. It is capable of autonomously perceiving information, analyzing issues, generating recommendations, and executing tasks across functions including procurement, supplier management, demand forecasting, inventory control, production scheduling, logistics and transportation, risk monitoring, and supply chain collaboration. Unlike traditional supply chain management software that relies primarily on fixed rules and manual operations, supply chain AI agents can integrate with ERP, WMS, and TMS systems, procurement platforms, and external market data. They utilize natural language interaction to handle tasks such as anomaly detection, order tracking, supplier inquiries, inventory replenishment, delivery alerts, and scenario simulation, while orchestrating cross-system workflows subject to access controls and human oversight mechanisms.
The market for enterprise supply chain AI agents is primarily driven by factors such as increasing supply chain complexity, the need for cost reduction and efficiency improvements, frequent external risks, and the maturation of generative AI technology. Challenges—including global sourcing, multi-tier supplier networks, demand volatility, logistics uncertainties, and inventory cost pressures—have created a demand for real-time, proactive decision-making tools. Meanwhile, the prevalence of manual tasks in traditional supply chain systems—such as data queries, data consolidation, email-based communication, and repetitive approval workflows—offers clear opportunities for AI agent automation. Furthermore, the continuous improvement of enterprise data infrastructure, alongside the widespread adoption of cloud computing, APIs, and supply chain control towers, has enabled these agents to access multi-source data and execute cross-system tasks. Looking ahead, as capabilities in model reasoning, industry-specific knowledge bases, data governance, and security mechanisms advance, supply chain AI agents will evolve from providing basic Q&A and recommendations toward autonomous planning, dynamic scheduling, supplier negotiation support, and end-to-end supply chain collaboration.
Report Scope
This report is a detailed and comprehensive analysis for global Enterprise Supply Chain AI Agent market. Both quantitative and qualitative analyses are presented by company, by region & country, by Type and by Application. As the market is constantly changing, this report explores the competition, supply and demand trends, as well as key factors that contribute to its changing demands across many markets. Company profiles and product examples of selected competitors, along with market share estimates of some of the selected leaders for the year 2025, are provided.
Key Features:
Global Enterprise Supply Chain AI Agent market size and forecasts, in consumption value ($ Million), 2021-2032
Global Enterprise Supply Chain AI Agent market size and forecasts by region and country, in consumption value ($ Million), 2021-2032
Global Enterprise Supply Chain AI Agent market size and forecasts, by Type and by Application, in consumption value ($ Million), 2021-2032
Global Enterprise Supply Chain AI Agent market shares of main players, in revenue ($ Million), 2021-2026
The Primary Objectives in This Report Are:
To determine the size of the total market opportunity of global and key countries
To assess the growth potential for Enterprise Supply Chain AI Agent
To forecast future growth in each product and end-use market
To assess competitive factors affecting the marketplace
This report profiles key players in the global Enterprise Supply Chain AI Agent market based on the following parameters - company overview, revenue, gross margin, product portfolio, geographical presence, and key developments. Key companies covered as a part of this study include SAP, Oracle, Microsoft, Blue Yonder, Palantir, Manhattan Associates, Kinaxis, Infor, Coupa, o9 Solutions, etc.
This report also provides key insights about market drivers, restraints, opportunities, new product launches or approvals.
Enterprise Supply Chain AI Agent market is split by Type and by Application. For the period 2021-2032, the growth among segments provides accurate calculations and forecasts for Consumption Value by Type and by Application. This analysis can help you expand your business by targeting qualified niche markets.
Market segmentation
Market segment by Type
Cloud-based
On-premises
Market segment by Function
Analytical Agents
Autonomous Decision-Making Agents
Collaborative Multi-Agent Systems
Market segment by Application
Large Enterprises
Small and Medium-sized Enterprises
Market segment by players, this report covers
SAP
Oracle
Microsoft
Blue Yonder
Palantir
Manhattan Associates
Kinaxis
Infor
Coupa
o9 Solutions
ServiceNow
IBM
Celonis
UiPath
C3 AI
GEP
project44
FourKites
Ivalua
JAGGAER
Authine
Kingdee
Market segment by regions, regional analysis covers
North America (United States, Canada and Mexico)
Europe (Germany, France, UK, Russia, Italy and Rest of Europe)
Asia-Pacific (China, Japan, South Korea, India, Southeast Asia and Rest of Asia-Pacific)
South America (Brazil, Rest of South America)
Middle East & Africa (Turkey, Saudi Arabia, UAE, Rest of Middle East & Africa)
Chapter Outline
Chapter 1, to describe Enterprise Supply Chain AI Agent product scope, market overview, market estimation caveats and base year.
Chapter 2, to profile the top players of Enterprise Supply Chain AI Agent, with revenue, gross margin, and global market share of Enterprise Supply Chain AI Agent from 2021 to 2026.
Chapter 3, the Enterprise Supply Chain AI Agent competitive situation, revenue, and global market share of top players are analyzed emphatically by landscape contrast.
Chapter 4 and 5, to segment the market size by Type and by Application, with consumption value and growth rate by Type, by Application, from 2021 to 2032.
Chapter 6, 7, 8, 9, and 10, to break the market size data at the country level, with revenue and market share for key countries in the world, from 2021 to 2026.and Enterprise Supply Chain AI Agent market forecast, by regions, by Type and by Application, with consumption value, from 2027 to 2032.
Chapter 11, market dynamics, drivers, restraints, trends, Porters Five Forces analysis.
Chapter 12, the key raw materials and key suppliers, and industry chain of Enterprise Supply Chain AI Agent.
Chapter 13, to describe Enterprise Supply Chain AI Agent research findings and conclusion.
Summary:
Get latest Market Research Reports on Enterprise Supply Chain AI Agent. Industry analysis & Market Report on Enterprise Supply Chain AI Agent is a syndicated market report, published as Global Enterprise Supply Chain AI Agent Market 2026 by Company, Regions, Type and Application, Forecast to 2032. It is complete Research Study and Industry Analysis of Enterprise Supply Chain AI Agent market, to understand, Market Demand, Growth, trends analysis and Factor Influencing market.