As digital transformation is gaining momentum, AI is emerging as the strategic backbone that builds critical linkages and optimizes complex, multi-modal supply chains. The era of reactive supply chains has run its course. AI is now driving a fundamental shift not just from reactive to predictive, but increasingly toward prescriptive logistics, where decisions can be made autonomously, in real time. In fact, synchronising air, sea, rail, and road transport will require more than just automation, it demands intelligent systems that can analyse vast data sets, anticipate disruptions, and recommend the most efficient action plans across modes.

However, building this kind of operational intelligence requires more than just technology. It calls for robust digital infrastructure, a disciplined approach to data governance, and AI models trained specifically for logistics models that understand nuances like port congestion, seasonal demand surges, or last-mile delays. And when dealing with sensitive cargo like pharmaceuticals or defence materials, the need for explainable, auditable AI frameworks becomes even more crucial. AI adoption enhances transparency, trust, and traceability.

At a broader scale, the convergence of AI, IoT, and automation platforms perfectly complements infrastructure development initiatives like PM Gati Shakti, paving the way for building a logistics network that is resilient, sustainable, and future-facing. 

As we look ahead, the industry’s ability to scale AI responsibly will define the service delivery capacity and capability of global supply chain in terms of speed, efficiency and resilience.

Kapil Mahajan, Global Chief Information & Technology Officer – IT, Allcargo Logistics