India Supply Chains Test AI Readiness Levels

India’s logistics industry is drawing fresh attention after large-scale investments in artificial intelligence were announced at a national technology summit, signalling a shift towards smarter supply chains. The development is significant for a sector critical to urban economies, where high costs and inefficiencies continue to affect goods movement, inflation, and the sustainability of city infrastructure.

Valued at over $300 billion, India’s logistics ecosystem underpins manufacturing, e-commerce, and urban consumption. Yet, logistics expenses remain elevated at around 13–14 per cent of GDP well above global benchmarks. This cost burden is increasingly shaping conversations around AI in logistics, particularly as cities grapple with congestion, emissions, and land constraints linked to freight movement.

Industry experts indicate that the promise of AI in logistics lies in its ability to optimise routes, reduce idle capacity, and improve warehouse efficiency. However, these gains depend heavily on the quality of underlying data systems. Much of India’s supply chain still operates through fragmented digital tools, manual records, and isolated platforms, limiting the ability of AI systems to generate reliable insights. A senior logistics technology executive noted that predictive systems require continuous, standardised data flows from shipment tracking to delivery timelines to function effectively. Without this, algorithm-driven decisions risk becoming inconsistent or incomplete, particularly in complex urban supply chains.

Fragmentation remains a defining feature of the sector. A large share of transport operators run small fleets, often with limited access to digital tools. While this decentralised structure creates inefficiencies, it also presents an opportunity. Analysts suggest that digital freight platforms powered by AI could aggregate this distributed capacity, improving vehicle utilisation and reducing empty return trips one of the biggest contributors to logistics costs and carbon emissions. Warehousing is another area where transformation is underway. Automated inventory systems and AI-enabled management tools are gradually being introduced in logistics parks around major cities. These systems can enhance throughput, reduce errors, and improve land use efficiency an increasingly important factor in dense urban regions where industrial land is scarce.

However, the shift towards automation is also reshaping employment patterns. With millions employed across transport and warehousing, the transition to technology-driven operations is expected to change job roles rather than eliminate them. Industry observers highlight the growing need for workforce training in digital tools, data handling, and systems management to ensure inclusive growth. Governance is emerging as another key concern. As AI begins to influence decisions such as freight allocation and route planning, experts stress the need for transparency and accountability frameworks. Human oversight, audit trails, and clear escalation mechanisms are likely to remain essential in maintaining trust in automated systems.

Looking ahead, the success of AI adoption in logistics will depend less on investment scale and more on systemic readiness. Strengthening digital infrastructure, improving data interoperability, and building workforce capabilities could determine whether AI becomes a transformative force or remains an underutilised tool in shaping efficient, low-carbon urban supply chains.

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India Supply Chains Test AI Readiness Levels