AI Agents in Logistics Are Moving From Visibility to Decision-Making

For decades, logistics systems promised visibility. Dashboards, alerts, and track-and-trace platforms showed where goods were, but rarely told managers what to do next. The result: operations teams buried in manual procurement, reactive firefighting, and rising costs. As global supply chains remain under pressure, the industry is now asking whether AI can step beyond monitoring and into active decision-making.

Nitin Jayakrishnan, CEO of Pando, says the greatest near-term opportunity lies in cutting spend while building resilience. “The biggest opportunity we’ll see in the near future is not just how AI agents can maximize logistics operations but how it can help minimize operational spend across the enterprise. Global enterprises put major dollars towards logistics, but most procurement and spend management decisions are still largely manual, siloed and reactive. When we bring in AI agents, companies can begin to analyze real-time data across suppliers, contracts and market conditions and then actively recommend or even execute optimized spend decisions.”

That means AI agents not only benchmark carrier rates but also enforce supplier compliance, flag overcharges, and run scenario analysis on alternative procurement strategies. In practice, every dollar invested in automation is meant to return directly to the bottom line.

Adoption, however, is far from straightforward. Jayakrishnan points to trust as the biggest hurdle: “Pilots often deliver strong results in narrow use cases, but scaling means embedding AI agents into the complexity of enterprise systems, policies and people.” Data readiness and change management are the sticking points. Leaders assume they need perfect data before starting, but he argues that iterative adoption—layering explainability into projects—builds confidence faster. And while fears of automation replacing jobs remain, the reality is that AI agents act more like sidekicks, augmenting human expertise rather than replacing it.

Nitin Jayakrishnan, CEO of Pando

By 2026, the expectation is that AI agents will take over most transactional logistics work. Human teams will shift from execution to orchestration—focusing on supplier relationships, strategic planning, and innovation while machines handle scale. “We’re not going to see humans disappear from supply chain management, they’ll just move up the value chain. It will be a partnership where AI agents handle execution at scale, and people provide the context, creativity and judgment that machines can’t replicate.”

Competitors such as o9 Solutions, Blue Yonder, and FourKites are making similar bets, each pitching AI agents as the next leap beyond visibility. For shippers, the stakes are clear: those who continue to drown in spreadsheets and exception queues risk losing both cost competitiveness and resilience, while those who let machines make more of the calls may finally get ahead of disruption.

For tips, leaks or anonymous sourcing: editor@thesupplychainer.com