Udit Agarwal

Session Speaker

Biography

Udit Agarwal is a Product Leader at Google, where he currently oversees the Consumer Shopping Compliance and infrastructure platforms to drive compliance, consistency, accuracy and developer velocity for Shopping experiences across multiple Google surfaces. 
Previously at Google, he led the anti-money laundering platform for Google-wide payments, developing financial investigative tools and backend infrastructure. Before joining Google, Udit was a Staff Product Manager at Walmart eCommerce, where he led a marketplace seller API platform enabling large scale 3rd party sellers to sell on the Walmart marketplace. He also launched the MVP of an autonomous delivery platform. His professional achievements have been recognized with the Google “Tech. Impact” award and the Walmart eCommerce ‘Make a Difference’ award.
He holds an MBA with Dean’s Honors from Columbia Business School and a Bachelor of Science in Chemical Engineering, cum laude, from the University of Michigan. Outside of his corporate work, Udit is a member of the Board of Trustees for the NGO Hardayal Viklang Kendra, keen golfer and an avid hiker and has completed multiple high-altitude treks in the Himalayas.

Abstract

Title: Developing a transformation AI Product Strategy for eCommerce

Abstract: Online shopping has become a daily habit for millions, yet the journey—from selection to payment, fraud checks, and returns—remains far from seamless. With the rise of AI, retail is on the cusp of adopting autonomous actions that simplify these complex transaction lifecycles.

Udit deconstructs the strategy behind AI-native retail. He will move beyond the frontend user experience to reveal the backend infrastructure required to scale, including the critical trade-offs between model latency, GPU investment, and unit economics. What You Will Learn 1. Aligning AI with Business Value: How to map AI enablement to specific stakeholders based on their scale, cost, and revenue contribution to the business. 2. Rethinking the Business Model: Strategies to transform the entire chain—from hyper-personalized frontend experiences to highly predictive, low-cost fulfillment. 3. Infrastructure as Strategy: Why successful transformation requires deep focus on infrastructure investments (GPUs, TPUs) to deploy models with minimal latency.

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