From logistics to intelligence: Building the next generation of commerce

By Praful Poddar, Chief Product Officer, Shiprocket

For most of its history, logistics has been an execution function. An order was placed, a shipment was allocated, a route was planned, and a package was delivered. Success was largely measured by whether it reached the customer on time and at an acceptable cost.

That model worked when commerce itself was relatively linear. It is much harder to sustain today!

A single customer transaction can involve inventory spread across multiple locations, several fulfilment options, different logistics networks, a delivery promise made at checkout and, increasingly, a customer or seller in another country. Demand can shift by the hour. Capacity can change just as quickly. A route that was optimal in the morning may no longer be the right one by afternoon.

The challenge is therefore no longer simply moving goods efficiently. It is deciding, continuously, what the most intelligent thing to do next.

That is where I believe the next generation of commerce infrastructure is being built. The transition is from logistics that executes decisions to logistics that helps make them.

This distinction matters particularly in a market like India. Its commerce ecosystem is inherently fragmented, with multiple logistics networks, thousands of PIN codes, diverse fulfilment models and sharply different customer expectations across regions and categories. Fragmentation is unlikely to disappear. The more meaningful opportunity is to make that fragmentation work as one connected system.

That requires an intelligence layer. Traditionally, a logistics decision could be based on serviceability, price or historical courier performance. But performance is not a fixed attribute. It can vary by PIN code, shipment profile, capacity and operating conditions.

A courier that performs exceptionally well across a network may not be the best choice for a specific location or shipment at a given moment. This is why intelligent routing has to move beyond static rules.
We have seen the value of this shift first-hand. Systems such as Radar use live signals at the courier and PIN code levels to identify delivery risks and inform routing decisions. Instead of looking backwards only after a shipment has failed, the network can increasingly identify the conditions associated with failure and act before the customer experiences the problem.

That is a fundamental change in how technology participates in logistics. The objective is no longer simply to understand what happened. It is to use what is happening now to decide what should happen next.

The same principle is transforming fulfilment. The warehouse of the future is unlikely to be a single large facility serving an entire geography. It is more likely to be a network of interconnected inventory nodes, including warehouses, dark stores and other fulfilment locations, each capable of serving different demand pools.

What makes this model powerful is not the physical infrastructure alone. It is the intelligence connecting it.

When inventory visibility is real-time, and order allocation can consider demand, location, availability and delivery requirements, the network can determine which node should fulfil an order rather than relying on a predetermined hierarchy. A common inventory pool can increasingly serve different commerce models, from D2C and marketplaces to B2B, quick commerce and omnichannel demand.

This is also changing the role of the customer experience. The logistics network increasingly influences the transaction before the order is even placed. A delivery promise shown at checkout is no longer simply an estimated date. For that promise to be credible, it has to reflect inventory availability, location, serviceability, fulfilment capacity and network performance.

The customer sees a date. Behind that date sits a complex technology decision. This is one of the most important changes in commerce infrastructure. Logistics is moving upstream. It is no longer simply the final stage of a transaction; it is becoming part of the proposition that determines whether a customer chooses to complete that transaction in the first place.

The same architecture becomes even more important when commerce crosses borders. For an Indian business, selling to a customer in Bengaluru and to one in London may start with the same digital storefront, but the logistical complexity is fundamentally different. International carriers, customs, documentation, duties, shipping modes, tracking and destination-market requirements all enter the equation.

Technology has to absorb that complexity. That is the thinking behind the evolution of platforms such as ShiprocketX, which now enable businesses to reach more than 220 countries and territories and have expanded beyond parcel exports into international air and ocean freight. The objective is not simply to provide another shipping option. It is to make cross-border commerce accessible without requiring every merchant to become an expert in international logistics.

This principle has been consistent in our experience of building commerce infrastructure: complexity should increasingly sit behind the technology, rather than with the merchant. It is also why the conversation around AI in logistics needs to move beyond automation. Automation makes an existing process faster. Intelligence can change the process itself.

The distinction is important. A system that automates route planning is useful. A system that continuously learns which routing decision is likely to produce the best outcome under changing conditions is fundamentally different. A fulfilment centre that processes orders automatically is valuable.

A network that can determine which fulfilment node should process an order based on live demand and inventory is even more powerful.

The real opportunity lies in connecting these decisions. Demand informs inventory. Inventory informs fulfilment. Fulfilment informs the delivery promise. The delivery promise informs routing. The outcome of the shipment generates new data that improves the next decision.

The result is a decision loop rather than a linear supply chain.

That, in my view, is the more meaningful role of AI in commerce. Not replacing the physical network, but making the network increasingly aware of itself.

For years, the industry focused on moving goods faster. That remains important, but speed alone is becoming less differentiated. The next competitive advantage will come from knowing where inventory should sit, which fulfilment node should serve an order, which logistics option is most appropriate, what delivery promise can genuinely be made and how the network should respond when circumstances change.

The defining question for commerce infrastructure is therefore changing.

It is no longer simply: Can we move this order faster?

It is: Given everything we know about demand, inventory, capacity, geography and the network, what is the smartest thing to do next?

That is the transition from logistics to intelligence. And as commerce becomes increasingly distributed, omnichannel and global, the companies that can connect those decisions will shape not just how goods move, but how commerce itself operates.