Agentic AI in Supply Chain and Logistics

REPORT HIGHLIGHTS

Global Agentic AI in Supply Chain and Logistics Market to Reach US$22.8 Billion by 2032

The global market for Agentic AI in Supply Chain and Logistics estimated at US$8.5 Billion in the year 2025, is expected to reach US$22.8 Billion by 2032, growing at a CAGR of 15.2% over the analysis period 2025-2032. Software Platforms Component, one of the segments analyzed in the report, is expected to record a 14.8% CAGR and reach US$9.9 Billion by the end of the analysis period. Growth in the AI-enabled Hardware Systems Component segment is estimated at 17.7% CAGR over the analysis period.

The U.S. Market is Estimated at US$2.5 Billion While China is Forecast to Grow at 14.4% CAGR

The Agentic AI in Supply Chain and Logistics market in the U.S. is estimated at US$2.5 Billion in the year 2025. China, the world`s second largest economy, is forecast to reach a projected market size of US$3.9 Billion by the year 2032 trailing a CAGR of 14.4% over the analysis period 2025-2032. Among the other noteworthy geographic markets are Japan and Canada, each forecast to grow at a CAGR of 14.0% and 13.2% respectively over the analysis period. Within Europe, Germany is forecast to grow at approximately 11.3% CAGR.

Global Agentic Artificial Intelligence (AI) in Supply Chain and Logistics Market - Key Trends & Drivers Summarized

How Is Agentic AI Redefining Intelligence Across End-to-End Supply Chain Networks?

Agentic Artificial Intelligence is transforming supply chain and logistics operations by enabling autonomous systems that can reason, plan, and act across highly interconnected and continuously changing networks. Unlike traditional supply chain analytics or rule-based planning tools that focus on forecasting or optimization in isolation, agentic AI systems function as goal-oriented agents capable of interpreting objectives such as service level adherence, cost optimization, or resilience improvement and determining how to achieve them dynamically. These systems continuously ingest data from suppliers, manufacturing sites, warehouses, transportation networks, and demand channels to maintain real-time situational awareness. By retaining contextual memory across planning cycles and execution stages, agentic AI can anticipate disruptions, evaluate trade-offs, and initiate corrective actions without waiting for human intervention. This capability is reshaping supply chains from linear, forecast-driven structures into adaptive ecosystems that respond continuously to demand variability, capacity constraints, and external shocks. As global supply networks become more distributed and digitized, agentic AI is emerging as the intelligence layer that synchronizes planning, execution, and monitoring into a unified operational framework.

Why Are Enterprises and Logistics Providers Accelerating Agentic Adoption?

Enterprises and logistics providers are accelerating adoption of agentic AI to manage rising complexity, volatility, and scale across supply chain operations. Globalization, multi-tier supplier networks, and omnichannel fulfillment models have increased the difficulty of coordinating decisions using traditional planning systems. Agentic AI systems address these challenges by autonomously orchestrating demand planning, inventory positioning, production scheduling, and transportation routing across multiple nodes. In logistics operations, these systems dynamically allocate resources, optimize carrier selection, and adjust delivery plans based on real-time conditions such as congestion, weather, and capacity availability. Warehousing environments are also adopting agentic AI to coordinate picking, packing, and automation systems in alignment with inbound and outbound flows. The ability of agentic systems to learn from execution outcomes and refine decision strategies over time is enabling organizations to operate with greater agility while reducing dependency on manual planning and exception management.

What Role Does Agentic AI Play in Resilience, Visibility, and Execution Optimization?

Agentic AI is playing a central role in improving supply chain resilience, visibility, and execution optimization by enabling continuous, autonomous decision-making. Supply chain disruptions driven by geopolitical events, natural disasters, and demand shocks have exposed the limitations of static contingency planning. Agentic AI systems continuously monitor risk signals across suppliers, transportation routes, and markets to identify emerging threats and proactively adjust plans. These systems evaluate alternative sourcing, routing, and inventory strategies in real time, balancing cost, service, and risk considerations. In execution environments, agentic AI autonomously manages exceptions such as delays, shortages, and capacity imbalances by coordinating actions across partners and systems. The integration of agentic intelligence with control towers and digital twins is further enhancing visibility by enabling simulation and validation of decisions before execution. This capability is making supply chains more responsive and robust in the face of ongoing uncertainty.

What Is Powering Market Expansion Across Supply Chain and Logistics?

The growth in the Agentic Artificial Intelligence in Supply Chain and Logistics market is driven by several factors that are directly linked to operational volatility, network complexity, and evolving customer expectations. Increasing frequency of supply disruptions is driving demand for autonomous systems capable of real-time re-planning and execution. Expansion of e-commerce and omnichannel fulfillment is increasing pressure on logistics networks to deliver speed and reliability at scale. Rising transportation and labor costs are accelerating adoption of agentic AI that can optimize resource utilization and reduce inefficiencies. Growing adoption of automation, sensors, and connected platforms is strengthening the data foundation required for agentic decision-making across supply chains. Additionally, heightened expectations for visibility and responsiveness from customers and partners are pushing organizations to deploy continuous intelligence rather than periodic planning tools. Together, these drivers are positioning agentic AI as a core capability for next-generation supply chain and logistics operations.

SCOPE OF STUDY:

The report analyzes the Agentic AI in Supply Chain and Logistics market in terms of units by the following Segments, and Geographic Regions/Countries:

Segments:
Component (Software Platforms Component, AI-enabled Hardware Systems Component, Services Component); Application (Demand Forecasting & Planning Application, Warehouse & Fulfillment Optimization Application, Transportation Routing & Fleet Management Application, Procurement & Sourcing Automation Application, Last-Mile Delivery Orchestration Application, Other Applications); End-Use (Retail & E-Commerce End-Use, Manufacturing End-Use, Food & Beverages End-Use, Healthcare & Pharmaceuticals End-Use, Automotive End-Use, Other End-Uses)

Geographic Regions/Countries:
World; USA; Canada; Japan; China; Europe; France; Germany; Italy; UK; Rest of Europe; Asia-Pacific; Rest of World.

SELECT PLAYERS -

• Blue Yonder, Inc.
• C3.ai, Inc.
• ClearMetal, Inc.
• Coupa Software Incorporated
• Dematic Corp.
• Elementum, Inc.
• Flexport, Inc.
• FourKites, Inc.
• Kinaxis Inc.
• Locus.sh (Locus Logistics Inc.)
• Manhattan Associates, Inc.
• o9 Solutions, Inc.
• Project44, Inc.
• Shipwell, Inc.
• Turvo Inc.

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