Autonomous Warehouse Intelligence: How Agentic AI Can Transform Operations Through Self-Directed Inventory, Picking, and Maintenance Decision-Making

SPEAKERS

Prashanth Cecil General Manager, Amazon

ABOUT THE SESSION


Prashanth Cecil, General Manager at Amazon in Tracy, California, is a seasoned supply chain leader with over 15 years of experience driving operational transformation across retail, consumer goods, and automotive sectors. With a career that includes leadership roles at Procter & Gamble and Suzuki Motor Corporation, Prashanth has consistently delivered scalable growth, operational excellence, and technological advancement. At Amazon, he has built deep expertise in warehouse automation, lean operations, and end-to-end supply chain optimization. A Certified Supply Chain Professional with a Master’s in Supply Chain Management from the University of Michigan’s Ross School of Business, he combines technical acumen with strategic vision. In his upcoming session, Prashanth will share insights on Autonomous Warehouse Intelligence: How Agentic AI Can Transform Operations Through Self-Directed Inventory, Picking, and Maintenance Decision-Making.

Prashanth Cecil will share his expert views on the transformative potential of agentic AI in warehouse operations, beginning with a clear definition of agentic AI capabilities and how they differ from traditional automation—focusing on autonomous decision-making and the ability to execute multi-step tasks independently. He will demonstrate how intelligent inventory management agents can optimize stock levels, predict demand patterns, and coordinate replenishment seamlessly across systems. Prashanth will also explore autonomous picking optimization, where AI agents dynamically route workers, adjust workflows in real time, and self-correct using operational feedback. Additionally, he will present predictive maintenance agents that monitor equipment health, proactively schedule repairs, and manage maintenance tasks without human input—unlocking a new era of warehouse intelligence.


Key Topics-

• Define agentic AI capabilities and differentiate from traditional automation, highlighting autonomous decision-making and multi-step task execution in warehouse environments
• Demonstrate intelligent inventory management agents that autonomously optimize stock levels, predict demand patterns, and coordinate replenishment across multiple systems
• Explore autonomous picking optimization where AI agents dynamically route workers, adjust workflows in real-time, and self-correct based on operational feedback
• Present predictive maintenance agents that monitor equipment health, schedule repairs proactively, and coordinate maintenance activities without human intervention
   

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