Agentic AI Liability: Autonomous Supply Chain Decisions Expose Contractual Gaps for Enterprise Deployers

As enterprises transition from predictive AI recommendations to Agentic AI—systems capable of making and executing autonomous decisions with minimal or no human supervision—they face a massive, unhedged operational and legal risk. While earlier AI tools flagged anomalies or suggested actions for human review, the newest agentic systems are designed to act autonomously, placing purchase orders, adjusting safety stock levels, selecting carriers, and re-routing shipments in real time.

Real-World Adoption and the "Agentic" Shift

The adoption of autonomous agentic systems is accelerating rapidly in supply chain and logistics operations. For example:

• Walmart now utilizes agentic AI for autonomous inventory replenishment and shipment re-routing across its massive fulfillment network.
• Flexport utilizes AI agents to autonomously manage approximately 40% of its freight forwarding operations, including dynamic shipment optimization and real-time exception handling during logistics disruptions.

While these systems offer substantial benefits—such as machine-speed reaction times and reduced labor costs—their autonomous nature introduces severe operational risks. If an agent misinterprets a data lag, misreads duplicated demand data, or makes a flawed routing decision, the resulting financial and physical damages can be immediate and catastrophic.

The Contractual Liability Gap

A May 20, 2026 legal analysis by Foley & Lardner warns that standard enterprise technology and SaaS agreements are fundamentally unsuited for agentic AI deployments, leaving enterprise deployers heavily exposed:

1. Inadequate Liability Caps: Standard AI vendor contracts typically cap liability at the annual fees or subscriptions paid. However, a single errant decision by an autonomous agent (e.g., triggering a plant-wide line stoppage or ordering millions of dollars in excess inventory) can cause losses that dwarf the annual software fee.
2. Consequential Damages Waivers: Standard agreements almost universally waive consequential, indirect, or special damages. Yet, the precise harms an autonomous agent is most likely to cause—such as plant downtime, expedited air freight charges, carrying costs for excess inventory, or lost production—are classified as consequential damages and would be completely barred from recovery.
3. The Multi-Party Causation Challenge: Proving causation in an agentic failure is exceptionally complex. If an agent makes a disastrous decision, the deployer must untangle whether the failure stemmed from the AI model's underlying logic, flawed data inputs, improper configuration, or lack of human oversight. This can simultaneously implicate the software vendor, third-party data providers, internal IT teams, and external system integrators.

As Foley & Lardner highlights:

"Standard AI vendor contracts typically cap liability at fees paid, which are often just annual subscription costs. However, a single errant autonomous decision can trigger losses many times over. Consequential damages waivers may bar recovery for the very harms—excess inventory, expedited freight, downtime, lost production—that agentic systems are most likely to cause." — Foley & Lardner LLP Client Alert

Mitigating Agentic Risk: A Blueprint for Legal and Risk Teams

To protect organizations from "runaway" autonomous agents, corporate legal and risk teams must move away from standard software procurement templates and negotiate specialized contractual architectures:

• Establish Autonomous Authority Limits: Define and hardcode strict thresholds (e.g., maximum dollar values per order, volume caps, or specific geographic routing restrictions) beyond which the agent cannot act autonomously and must escalate the decision to human review.
• Negotiate Agent-Specific Liability Carve-outs: Push for carve-outs from consequential damages waivers and higher, customized liability caps specifically for damages resulting from unauthorized or errant autonomous actions.
• Mandate Override and "Kill-Switch" Protocols: Contracts should contractually obligate the vendor to provide real-time monitoring dashboards and manual override capabilities, clearly allocating liability to the vendor if these controls fail or are unavailable.
• Address Data Quality and Validation: Since flawed data inputs are the primary cause of erroneous agent decisions, contracts must clearly allocate data quality responsibilities, specifying which party is responsible for validation and what happens when input quality falls below agreed-upon thresholds.
• Maintain Comprehensive Decision Logs: Require the system to maintain unalterable, audit-ready logs detailing exactly why the agent made a specific decision. This is critical for both defending against third-party claims and pursuing recourse against vendors.