Inventory Decisions Under Pressure: AI Platforms Shift Focus From Visibility to Trade-Off Optimization

Sudden disruptions to shipping routes are forcing supply chain teams to make faster, higher-stakes inventory decisions with incomplete information. When transit times shift, costs rise, and capacity tightens, the challenge is no longer just tracking shipments but determining which products to prioritize, delay, or reroute without compromising revenue or service levels.

The operational impact is immediate. Without clear visibility into inventory positions and order commitments, companies risk overreacting to disruptions or missing critical intervention windows. As volatility becomes more frequent, the ability to quantify trade-offs between cost, service, and availability is becoming a core capability rather than a planning exercise.

In response to a media query from The Supply Chainer, Rafa Santiago, Chief Operating Officer and Co-Founder of Nauta, said: “AI cannot reopen a major trade route. What it can do is help shippers make better decisions with the options they actually have.”

“For example, if a key route becomes unreliable, AI can surface which inbound shipments contain critical SKUs, which have available substitutes, and which can tolerate delay. AI can also quantify the cost and service impact of expediting certain orders or choosing different transportation providers, projecting landed cost changes from surcharges or longer transit times and determining whether those costs outweigh the revenue risk of a stockout.”

Santiago pointed to a broader issue: “Without structured data, teams are forced to rely on manual spreadsheets and tribal knowledge, which slows response time precisely when speed matters most.”

Rafa Santiago, Chief Operating Officer and Co-Founder of Nauta

On priorities during disruption, he added: “All three matter, but they only work if they are built on a single foundation of accurate, harmonized data across the supply chain.”

“Network-wide visibility is the starting point. To effectively respond to any disruption, you have to know what inventory is on hand, what is in transit, and what is committed to customers. Visibility also needs to be at the SKU level, not just container or shipment level, because financial exposure and service risk are driven by specific products.”

“Scenario modeling becomes critical once that visibility exists. Leaders need to understand what different response options will cost, for example, what is the impact of diverting cargo or accepting delays? How will each decision affect landed cost and working capital?”

“Predictive inventory positioning is what reduces risk before disruptions occur. Over the course of a year, companies with structured data can forecast demand more accurately, which allows them to identify where buffer stock is actually needed, avoiding both stockouts and excess inventory.”

“Structured, clean, harmonized data gives decision makers the ability to move from reactive firefighting to proactive management, minimizing risk across the entire operating cycle.”

The shift toward AI-driven decision support reflects a broader transition across supply chains, where visibility alone is no longer sufficient. As disruptions become more frequent, competitive advantage is increasingly defined by how quickly companies can translate data into coordinated, economically sound decisions.