Webinars
Agentic AI for Frontline Decision-Making: When Should Customer Conversations Stop?
Frontline employees constantly face a difficult judgment call: whether to continue a customer conversation or move on. Persist too long and valuable time is lost; disengage too early and promising opportunities may slip away.
In this webinar, we introduce a new agentic AI approach to real-time decision-making in customer interactions. Rather than generating scripts or replacing employees, an AI “stopping agent” observes live conversations and decides whether the interaction should continue or end.
We will discuss how generative AI can be trained to make sequential decisions under uncertainty and what this emerging class of action-oriented AI agents could mean for sales and customer-facing operations. Join us to learn how AI may help organizations rethink how frontline time and attention are allocated.
speaker
Eva Ascarza is the Jakurski Family Associate Professor of Business Administration in the Marketing Unit. She is the co-founder of the Customer Intelligence Lab at the D^3 institute at Harvard Business School. As a marketing modeler, Professor Ascarza uses tools from statistics, economics, and machine learning to answer relevant marketing questions. Her main research areas are customer management (with special attention to the problem of customer retention), Personalization and Targeting, Marketing AI, and algorithmic decision making. She uses field experimentation (e.g., A/B testing) as well as econometric modeling and machine learning tools not only to understand and predict patterns of behavior, but also to optimize the impact of firms’ marketing interventions.