By Sagar Shankaran, Founder of CallSphere
Shipping giants Flexport and Maersk deploy AI agents to optimize routes, manage inventory, and handle customs documentation autonomously, transforming global supply chain operations.
Key takeaways
Global supply chains move $28.5 trillion in goods annually across oceans, skies, rails, and roads, managed through an intricate web of shipping schedules, customs regulations, inventory systems, and handoff points that has historically required massive human coordination. That coordination model is being fundamentally disrupted as Flexport, Maersk, and other logistics leaders deploy AI agents that autonomously manage increasingly complex segments of the supply chain.
In March 2026, Flexport announced that its AI agent system now autonomously manages 40% of its freight forwarding operations, up from 8% in January 2025. Maersk, the world's second-largest container shipping company, revealed that AI agents handle routing decisions for 35% of its global container fleet. These are not pilot programs or demos — they are production systems managing billions of dollars in cargo.
"Supply chain is the perfect environment for agentic AI," said Ryan Petersen, CEO of Flexport. "It's a domain where thousands of decisions need to be made quickly based on incomplete information, where the cost of delays is enormous, and where the rules — customs regulations, carrier schedules, port capacities — are complex but structured enough for AI to learn."
Flexport's AI agent system, internally called "FlexAgent," orchestrates the entire lifecycle of a freight shipment from booking to delivery. The system comprises specialized agents that handle different aspects of the logistics workflow and coordinate through a central orchestration layer.
flowchart LR
INPUT(["User intent"])
PARSE["Parse plus<br/>classify"]
PLAN["Plan and tool<br/>selection"]
AGENT["Agent loop<br/>LLM plus tools"]
GUARD{"Guardrails<br/>and policy"}
EXEC["Execute and<br/>verify result"]
OBS[("Trace and metrics")]
OUT(["Outcome plus<br/>next action"])
INPUT --> PARSE --> PLAN --> AGENT --> GUARD
GUARD -->|Pass| EXEC --> OUT
GUARD -->|Fail| AGENT
AGENT --> OBS
style AGENT fill:#4f46e5,stroke:#4338ca,color:#fff
style GUARD fill:#f59e0b,stroke:#d97706,color:#1f2937
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When a customer submits a shipping request, the booking agent evaluates available routes across multiple carriers, considering factors that human freight forwarders typically juggle in their heads or on spreadsheets: transit time, cost, reliability history, carbon footprint, customs complexity for the specific cargo type, and current port congestion levels.
The agent queries real-time data feeds from ports, carriers, weather services, and AIS (Automatic Identification System) vessel tracking to build a dynamic picture of available options. It then presents the optimal route — or a set of ranked alternatives — to the customer, including predicted delivery windows with confidence intervals.
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"The AI consistently identifies routing options that our human brokers miss," said a Flexport operations executive. "Not because the humans aren't skilled, but because the agent can simultaneously evaluate 500 route combinations across 30 carriers with real-time data. No human can hold that many variables in working memory."
One of the highest-impact applications is autonomous customs documentation. International shipping requires precise completion of bills of lading, commercial invoices, packing lists, certificates of origin, and country-specific regulatory filings. Errors in these documents cause delays, fines, and cargo holds.
Flexport's customs agent generates and validates documentation by cross-referencing the cargo details against the harmonized tariff schedules of both the origin and destination countries, current sanctions lists, restricted goods databases, and bilateral trade agreement provisions. The system has reduced documentation errors by 87% compared to the manual process.
Perhaps the most impressive capability is the exception-handling agent, which monitors shipments in transit and autonomously responds to disruptions. When a vessel is delayed, a port experiences congestion, or weather threatens a route, the agent evaluates alternatives, rebooks cargo on different carriers or routes, updates customs documentation, notifies all stakeholders, and adjusts downstream logistics — all without human intervention.
In February 2026, when severe storms in the South China Sea disrupted shipping across Southeast Asia for 10 days, Flexport's exception-handling agent autonomously rerouted 2,300 containers across alternative paths, minimizing delays by an average of 4 days compared to manually managed shipments.
Maersk's approach focuses on fleet-level optimization — using AI agents to manage the routing, scheduling, and cargo allocation of its 700+ vessel fleet.
Maersk's routing agents continuously optimize vessel paths based on real-time fuel prices, weather patterns, port congestion, cargo demand, and environmental regulations. The agents adjust speed profiles to minimize fuel consumption while meeting delivery commitments — a practice called "slow steaming" that Maersk estimates saves $200 million annually in fuel costs.
The routing optimization is particularly sophisticated in its handling of multi-port itineraries, where the optimal sequence of port calls depends on cargo priorities, port availability, tide schedules, and berth reservations that change hourly.
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One of the logistics industry's most expensive problems is container repositioning — the movement of empty containers from locations where they've been unloaded to locations where they're needed for new cargo. An estimated 20% of all container movements globally are repositioning empty boxes.
Maersk's AI agents manage container repositioning across its global network, predicting demand imbalances weeks in advance and pre-positioning empty containers to minimize dead-heading. The system has reduced empty container movements by 15%, saving an estimated $400 million annually.
AI agents also monitor the condition of Maersk's fleet and intermodal equipment, analyzing sensor data from engines, refrigeration units, and structural components to predict maintenance needs before failures occur. The predictive maintenance agent schedules repairs during planned port calls, minimizing unplanned downtime and extending equipment life.
Flexport and Maersk are leading indicators of a broader transformation. Other major logistics players deploying AI agents include:
The deployment of AI agents in supply chain management carries significant risks that the industry is actively managing.
When AI agents manage critical logistics decisions, system outages can cascade through the supply chain. Both Flexport and Maersk have implemented redundancy architectures with human fallback procedures, but the increasing reliance on AI systems concentrates risk.
Customs regulations change frequently and vary dramatically across jurisdictions. AI agents must stay current with an ever-shifting regulatory landscape, and errors in customs compliance can result in significant fines and cargo seizures. Both platforms employ specialized regulatory monitoring teams that continuously update the agents' knowledge bases.
The automation of logistics coordination is affecting employment in freight forwarding, customs brokerage, and shipping operations. Industry estimates suggest that 30% of logistics coordination roles will be significantly altered by AI agents by 2028, with routine coordination work automated and human roles shifting toward exception management, relationship building, and strategic decision-making.
Despite these challenges, the efficiency gains are too large to ignore. Supply chain AI agents are not replacing the entire logistics workforce — they are handling the high-volume, data-intensive coordination work that has always been the bottleneck in global trade.
Written by
Sagar Shankaran· Founder, CallSphere
Sagar Shankaran is the founder of CallSphere, where he builds production AI voice and chat agents deployed across healthcare, hospitality, real estate, and home services. He writes about agentic AI, LLM engineering, and shipping voice agents that handle real calls in production.
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