Sidney Anderson
Artificial intelligence represents a fundamental disruption to marketing, yet existing research treats AI as an instrumental tool rather than an epistemological challenge. This paper makes an original theoretical contribution by reframing AI's impact as an epistemological transformation rather than solely as an adoption decision. Introducing a four-quadrant knowledge matrix distinguishing known knowns, known unknowns, unknown unknowns, and unknown knowns, the analysis reveals that AI amplifies exploitation of known knowns through automation, accelerates exploration of known unknowns through analytics, but paradoxically both reveals and generates unknown unknowns through emergent behaviors that reorganize markets unpredictably. Traditional uncertainty-reduction strategies prove inadequate for these inherently unpredictable disruptions. Building on Taleb's concept of antifragility, the paper argues marketing organizations should shift from knowledge optimization toward epistemic antifragility. The goal is to provide scholars with new frameworks for theorizing uncertainty under AI disruption, while offering managers and policymakers actionable guidance for building organizational capabilities that gain strength from disruption rather than simply attempting to eliminate it.