Uma Sawant

Uma Sawant

Research Director

About

Uma Sawant is an AI and Data Science leader at Flipkart, where she leads teams building large-scale personalization, recommendation, and user understanding systems. Previously, she held AI leadership roles at LinkedIn, working on products including Jobs, Learning, and Talent Marketplace. Her work focuses on translating cutting-edge AI research into production systems that deliver measurable business impact at internet scale. She is passionate about building human-centered AI and advancing the practice of applied machine learning in consumer products.

For two decades, personalization has largely meant ranking content, products, or actions based on past behaviour. Agentic AI creates a more ambitious possibility: systems that understand a user’s intent, reason across short- and long-term preferences, ask clarifying questions, use tools, and help the user accomplish a goal.

But turning a recommender system into a trusted personal agent is not simply an LLM integration problem. It requires a new architecture for user understanding, memory, planning, retrieval, recommendation, evaluation, and human control.

Drawing on lessons from building personalization and user-intelligence systems at large scale, this talk presents a practical blueprint for the agentic personalization layer. It explores what should be learned from behavioural data, what should be explicitly confirmed with users, how short-term intent should interact with long-term preferences, and where human agency must override algorithmic confidence.

The talk will also examine the product and organizational changes required to move from optimizing clicks to helping people make better decisions."

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