Technological advancements, for long, have been at the forefront of noticeable disruptions across sectors. Such is the case with the Indian logistics industry, which has been seen latching onto a big idea derived from tech innovation. In the 1990s, it was GPS tracking. In the 2000s, the focus shifted to Enterprise Resource Planning (ERP) systems. And like every wave before it, artificial intelligence (AI) is currently reshaping the country’s logistics ecosystem.
CEO
RapidShyp
Today, AI is dominating every boardroom talk, logistics event, and investor note. And why not? From late deliveries, rising freight costs, failed first attempts, poor demand planning, to customer complaints, it has emerged as the solution to every pain point in logistics. The excitement is quite understandable, especially with Indian eCommerce projected to reach $250 billion by 2030 and customer expectations soaring high. In such an environment, AI appears to be the perfect answer.
Yet there is a big difference between talking about AI and using it in a way that changes results on the ground. Is AI creating real business value in logistics, or is the sector still caught in the noise around it? Let’s find out.
What AI Is Actually Getting Right
The strongest use of AI in logistics today is not in flashy robots or fully automated warehouses. It is in small, practical decisions that happen thousands of times every single day. And nowhere is this more visible than in the twin problems of returns and delivery accuracy.
For any business operating in India, the return to origin (RTO) rate is one of the most damaging numbers on the balance sheet. When a shipment comes back undelivered, the business absorbs the forward freight cost, the reverse logistics cost, and the repackaging expense, all without making a single rupee. Compounding this is the equally damaging problem of inaccurate estimated delivery dates (EDD). When a customer receives a wrong delivery window at checkout, support tickets rise, cash on delivery cancellations go up, and brand trust takes a quiet but measurable hit.
This is where AI is making its most meaningful contribution. On intelligent shipping platforms that consolidate multiple courier partners into one system, predictive AI systems trained on buyer behaviour, address quality signals, courier lane performance, and real-time network conditions can generate an RTO risk score for individual orders before they leave the warehouse. A “high risk” order can now be flagged and acted upon, whether by confirming the address, nudging a COD buyer toward prepaid, or routing the shipment through a courier with a stronger track record for that specific pin code.
On the EDD front, these systems also factor in live courier delays and seasonal load patterns to display accurate delivery windows at checkout, directly reducing buyer anxiety on delivery timelines and cutting down the volume of support queries around order status. By integrating these AI-driven tools directly into the shipping workflow, a startup shipping its first 50 orders has the same algorithmic firepower as a conglomerate shipping 50,000.
The Overlooked Truth Behind Most AI Deployments
Here is what the conference keynotes rarely mention. AI is only as good as the data it receives. Without clean, structured, and reliable data, even the best AI tool will fail. India’s logistics network is fragmented by geography, seasonality, and product category. This means that a courier that performs well in Tier I cities may have a poor track record in Tier II towns during the monsoon season. So, without granular, pin-code level data feeding into AI models, the output is little more than a well-designed guess.
Today, many companies are investing in AI tools without fixing the basic problems in their operations. Rather than merely integrating AI tools, businesses must opt for a unified, digital platform that communicates with live data feeds across the whole ecosystem to streamline operations, predict potential problems, and enable data-informed decisions. That’s why data standardisation is the most critical step before advanced technology can deliver real value.
What the Next Three Years Will Separate
The global artificial intelligence (AI) in logistics market size is projected to grow to nearly $708 billion by 2034. This clearly highlights the accelerating adoption of AI in the logistics industry. But to maximise AI’s impact, businesses operating in this domain should first evaluate their data readiness and invest in data infrastructure before moving to automation.
The near-term opportunity in Indian logistics is not about deploying AI for its own sake. It is about solving specific, high-frequency problems that bleed cost every single day. This is why businesses need automated weight discrepancy resolution, predictive identification of likely return shipments before dispatch, and intelligent rate optimisation across carrier networks in real time. These services are no longer science fiction. Today, tech-enabled platforms, built with a data-first approach, are quickly becoming the new normal for the industry.
The Only Question That Matters
India’s logistics costs have shown meaningful progress in recent years, dropping to approximately 7% of GDP from the long-standing benchmark of 13-14%, a shift that reflects the impact of structural policy reforms outlined in the National Logistics Policy. This is undoubtedly a significant achievement, but closing the gap is only half the story. The next challenge is sustaining and building on this progress through smarter, more consistent technology adoption across the sector.
Artificial intelligence will not rescue a logistics operation that has poor data hygiene, weak carrier relationships, or no feedback loop between delivery outcomes and future decisions. It will, however, give a well-run operation a meaningful edge in speed, cost, and reliability. So before asking whether a business is using AI, the sharper question worth asking is this. Is the AI doing something specific and measurable, or is it simply there because it looks good in a pitch deck? The answer to that question will tell the industry everything about where Indian logistics is genuinely headed and who is serious enough to lead it there.
–Authored by Ravi Goel, CEO, RapidShyp