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Anu
Rao
Sr Manager of Product Management Revenue
AWS
Anu Rao is a Senior Manager of Product Management at Amazon Web Services (AWS), where she leads product strategy for revenue systems that power reporting and sales compensation. She has more than 10 years of experience across product management, revenue operations, finance, and accounting, and currently leads the development of data products and technology that power sales reporting, quota setting, and compensation across AWS. More recently, Anu has led initiatives that power AI innovation for AWS RevOps, including the development of AI-powered revenue insights and a scalable revenue knowledge platform designed to make complex revenue and compensation information more accessible and actionable. She is particularly interested in how AI can transform Revenue Operations at scale — moving beyond individual use cases to rethink how teams access information, generate insights, and make decisions.
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21 January 2027 10:00 - 10:30
From Possibility to Practice: AWS’s Journey Toward AI-Powered Revenue Operations
Generative AI has enormous potential to transform Revenue Operations, but moving from that potential to practical, scalable applications inside a large enterprise is not straightforward. In this session, Anu Rao will share lessons from AWS’s journey toward AI-powered Revenue Operations. Drawing on early use cases across revenue insights, knowledge management, and operational workflows, she will explore how AWS is approaching the question of where AI can create meaningful value — and what teams are learning as they begin translating those opportunities into real capabilities. The session will examine some of the foundational questions enterprises face early in their AI journey: Where should you start? Which RevOps problems are actually well suited for AI? How do you ground AI in complex business data and policies? And how do you design for accuracy, trust, and adoption from the beginning? Attendees will leave with practical lessons for identifying high-value AI opportunities in Revenue Operations and building the foundations needed to move from experimentation toward scalable, AI-powered workflows.