Marketing World Models

Artificial intelligence has evolved from prediction and content generation to the simulation of entire environments. We introduce Marketing World Models (MWMs) as a new class of AI systems that are deployed through varying levels of environmental realism and agent autonomy to model and simulate customer behavior, firm strategies, and market evolution within synthetic marketing ecosystems. Drawing on strategic marketing capabilities frameworks, we explain how MWM represents a capacity enabler that empowers dynamic, architectural, cross-functional, and specialized marketing capabilities through synthetic agency and scalable counterfactuals. We then identify the foundational and design elements of MWMs, providing definitional clarity and grounding each element to current managerial use cases. Next, we provide a typology of MWMs based on a 2 × 2 matrix that crosses environmental realism and agent autonomy, elucidating the different manifestations of these AI ecosystems (LL: diagnostic sandboxes, LH: agentic decision engines, HL: world dreamers, HH: synthetic market ecosystems) and how they are suited to address different marketing problems. We conclude by providing an integrative framework of MWMs with testable propositions. Our work provides a marketing-specific foundation to deploy MWMs as strategic capability and explains how, under what conditions, and for what common marketing problems do world models create value for firms.