AI can explain a marketing concept. Can it apply that concept to a business decision, recognize a flawed assumption, or judge whether a recommendation will work?
Ray Burke, E.W. Kelly Professor of Business Administration at Indiana University's Kelley School of Business, joins Gabriella Mirabelli to discuss research published in the International Journal of Research in Marketing with co-authorsMaximilian Matthe and Alex Leykin. Their work examines how accurately general AI models hold and use foundational marketing knowledge.
Burke describes strong performance on recall and understanding, with weaker results as questions demand application, analysis, and evaluation. The conversation explores why identifying false statements can be harder than confirming true ones, how a user's assumptions shape the response, and why proprietary marketplace knowledge remains important when competitors have access to the same tools.
They also consider how junior marketers will develop expertise as AI takes on work that once provided practice. Burke offers practical suggestions for framing problems, requesting multiple perspectives, and critiquing recommendations before acting on them.
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