How AI Agents Speed Quality Decisions After a Cold Chain Excursion

When a temperature excursion surfaces in the field, quality teams need to know two things quickly: what the standard operating procedure (SOP) calls for and what actually happened on the ground. Closing that gap determines how fast a disposition decision can be made.

Speaking with Pharmaceutical Commerce at LogiPharma USA 2026, where he joined the panel "From SOP to Audit-Ready: AI-Enabled Exception Management Across the Pharma Supply Chain," Henry Ames, vice president of corporate strategy at Zoomlogi, says one approach his company sees with customers starts with digitizing the SOP itself. The SOP, he says, defines the outcome the customer is counting on, or as Ames puts it, it "is what the customer expects." The digitized workflow, along with the alerting and alarm processes that stem from it, then helps document exactly what takes place during an event.

Ames says some customers have set up an AI agent for each team member. Those agents handle many inbound calls and serve as the first point of escalation. When an agent is built, the success criteria for each conversation are clearly defined, and even the sentiment of a call can be specified in terms of the expected outcome.

That information is then pulled together and presented to the quality manager promptly and concisely, Ames says. The quality manager can then make the actual decision: whether the product needs to go into quarantine, or whether stability data supports an automatic release.

In that model, AI handles the first response and the documentation, while the disposition call stays with quality.

Watch the previous installment of Ames’ interview:

1. Why AI’s Clearest Supply Chain Wins Are in the Basics
2. What AI Changes, and Doesn’t, in Exception Handling