Inside Shiprocket’s AI awakening: How the ecommerce shipping unicorn is rewiring itself for an AI first future

Over the past year, Shiprocket has rewired its platform with AI-driven decision engines that touch nearly every stage of the delivery cycle. Its carrier allocation system, previously rules-based, is now powered by algorithms that evaluate real-time performance, location-level trends, and historical shipping behavior to determine the best delivery partner for each order.

IPO-bound Shiprocket, long known as the technology group behind thousands of D2C brands, is entering what CEO Sahil Goel describes as an “AI awakening,” a crucial shift that will redefine the company from a logistics enabler to an integrated intelligence layer for Indian commerce. In a detailed conversation with Business Today, Joel explained how the unicorn is rebuilding its core around AI to solve some of the sector’s most chronic inefficiencies.

At the heart of this transformation is Shiprocket’s belief that traditional logistics expansion – more delivery partners, more nodes, more surface area – is no longer the moat it once was. Instead, the advantage now lies in prediction and automation. “The future of logistics depends on AI,” says Joel. “Everything else will simply be too slow or too expensive.”

Over the past year, Shiprocket has rewired its platform with AI-driven decision engines that touch nearly every stage of the delivery cycle. Its carrier allocation system, previously rules-based, is now powered by algorithms that evaluate real-time performance, location-level trends, and historical shipping behavior to determine the best delivery partner for each order. The result is faster deliveries and fewer RTOs, which is critical for D2C brands operating on thin profit margins.

Goel points out that one of the biggest achievements is non-delivery report (NDR) mitigation. Using generative AI and conversational automation, Shiprocket’s system now interacts with customers to confirm addresses, reschedule deliveries, or detect fraud signals. “This was a big blind spot earlier,” he says. “AI gives us the ability to intervene within seconds rather than hours.”

Shiprocket also builds predictive models that help merchants plan inventory placement, anticipate demand spikes, and optimize dispatch from the right warehouse or delivery partner — an area that Joel believes will develop into a core revenue stream. The company has been quietly expanding its fulfillment footprint, but with an AI-first philosophy: “It’s not about adding more space; it’s about putting the right product in the right node before the order comes in.”

Joel stresses that Shiprocket’s AI transformation is not a side project but an organizational reset. Product teams are being restructured, engineers are being retrained, and data infrastructure is being rebuilt to support models that are constantly learning.

With e-commerce volumes rising in India and consumer expectations rising, Shiprocket believes that the winners in logistics in the next decade will not be those who transport the most parcels, but those who anticipate the next step even before the parcel leaves the shelf.