When Alice steps through the looking glass, the familiar turns strange: Words run backwards, the landscape becomes a chessboard, and “common sense” no longer guarantees the right move. Generative AI is creating a similar environment for marketing intelligence. What used to be slow becomes instant, what used to be expensive becomes cheap, and what used to be “good enough” can suddenly become risky. Yet, AI does not merely speed up existing routines. It reshapes the economics of insight, the workflow of research and the meaning of evidence. This special issue offers a managerial compass to navigate this new terrain.
The shifts in marketing intelligence are exciting, but also disruptive. AI not only shapes how things are done but raises entirely new questions. We address these questions and map where GenAI adds real value in consumer research – and where it wastes time or erodes credibility. We provide guidelines for using LLMs as autonomous agents, sparring partners, assistants, interviewers, moderators, probers and synthetic respondents from simulated “silicon samples.” And we add an important reality check on synthetic respondents: promising and improving, but best treated as support for early-stage or lower-stakes decisions rather than full substitutes for real-world data – at least for now.
So, where is the sweet spot? We translate these developments into rigorous managerial practices for deploying GenAI in market research and argue for human–AI collaboration that combines LLM speed with human judgment. And we present a high-ROI application example: AI-assisted idea screening, which helps turn idea overload into an innovation advantage without sacrificing strategic control.
All the contributions ultimately address the same challenge: navigating a looking-glass world where speed is cheap and confidence is the scarce resource. Enjoy reading and step behind the looking glass – without losing touch with the real world.