AI in pharma supply chains: From visibility to prediction and action | GPLS 2026
Knowing where a shipment is does not tell you whether it will arrive on time. Seeing an inventory number does not explain why demand has changed. How can pharmaceutical supply chains use AI to predict what could happen and act before a disruption affects delivery?
Business Session 4 at the Global Pharma Logistics Summit 2026 explores this shift from visibility to prediction. Moderated by Girish Bassavaraju, Country Head-India, Cosette Pharmaceuticals, the discussion brings together perspectives from pharmaceutical manufacturing, air cargo, warehousing, distribution and consumer healthcare.
Vipul Jain, Vice President – Supply Chain Strategy and Analytics, Intas Pharmaceuticals, assesses the industry’s progress. “We are good in terms of visibility now,” he says, while describing prediction as less mature and prescription as an area with much further to go. He argues that companies should improve data quality while beginning to use AI. The discussion also moves beyond operational efficiency to product portfolio strategy, workforce planning and change management.
For Vijayant Vikram Malik, Area General Manager, Indian Subcontinent, Etihad Cargo, the test is whether a prediction leads to timely intervention. “The value is created in the action based on the prediction,” he says. Weather may allow hours to respond, while handling and connectivity issues can leave only minutes. He explains how monitoring shipment milestones can help identify a potential failure, alert the relevant stakeholder and support corrective action before the milestone is missed.
Ashu Gupta, Vice President – Supply Chain, Koye Pharmaceuticals, points to the limited adoption of AI in outbound pharmaceutical supply chains. “First step would be to train the supply chain professionals on where to use AI,” she says. From inventory replenishment and forecasting to warehouse picking and truck loading, she discusses where AI could help and why management commitment, cost and the choice of application matter.
Vineet Kumar, Senior Manager, SCM-Warehouse & Logistics, Elanco, keeps human judgment central to the discussion. “I consider AI as a complementary tool,” he says. AI can support route changes, inventory risk assessment and warehouse efficiency. But fragmented data across ERP, warehouse management systems and transport management systems creates difficulties. Skilled people must assess the recommendations and make critical decisions.
Chintan Ghiya, Head Customer Care & Operations, Sanofi Consumer Healthcare India Ltd, speaking in his individual capacity, examines the missing demand signals between companies, distributors and retailers. “We are still very, very heavily dependent on what’s happening on just on the primary part,” he says. He shares an example from a previous role in which a simple AI tool read distributor information from Excel, PDF and text files. Better secondary sales and stock data could then support forecasting and supply planning.
The panel also examines data privacy, cybersecurity and the guardrails needed around AI tools. It closes by considering where AI could improve replenishment, reduce temperature excursions and help people protect product efficacy and temperature integrity.
