As an associate professor at Harvard Business School and cofounder of the Customer Intelligence Lab at the school’s Digital Data Design Institute, Ayelet Israeli’s work is focused on how data and technology can inform marketing strategy, as well as how generative AI can be a useful tool in eliminating algorithmic bias. One of the products of her recent work is a paper she coauthored with two Microsoft economists and researchers on how generative AI could be used to simulate focus groups and surveys to determine customer preferences. Ayelet joins Sam and Shervin to discuss the opportunities and limitations of generative AI in market research. She details how the research was conducted and how artificial intelligence technology could help marketers reduce the time, cost, and complexity associated with traditional customer research methods. Read the episode transcript here. Guest bio: Ayelet Israeli is the Marvin Bower Associate Professor of Business Administration in Harvard Business School’s Marketing Unit. She is also the cofounder of the school’s Customer Intelligence Lab at the Digital Data Design Institute. Her research focuses on data-driven marketing, with an emphasis on how businesses can leverage their internal data, customer data, and market data to improve outcomes. Her research interests include retail, pricing strategy, channel management, marketing analytics, and algorithmic bias. Israeli has a Ph.D. in marketing from the Kellogg School of Management at Northwestern University. Me, Myself, and AI is a collaborative podcast from MIT Sloan Management Review and Boston Consulting Group and is hosted by Sam Ransbotham and Shervin Khodabandeh. Our engineer is David Lishansky, and the coordinating producers are Allison Ryder and Sophie Rüdinger. Stay in touch with us by joining our LinkedIn group, AI for Leaders at mitsmr.com/AIforLeaders or by following Me, Myself, and AI on LinkedIn. We encourage you to rate and review our show. Your comments may be used in Me, Myself, and AI materials.