Human-AI Collaboration in Marketing Decision-Making: Enhancing Managerial Judgment or Creating Dependence?

Abstract

This article examines whether human-AI collaboration in marketing decision-making enhances managerial judgment or creates new forms of dependence. Adopting a systematic literature review of peer-reviewed studies published between 2018 and 2022, it synthesizes evidence on how marketers use AI tools to support tasks such as targeting, forecasting, and campaign optimization. The review identifies benefits of AI as an analytical and advisory partner, including improved data processing, pattern detection, and support for evidence-based strategies, alongside risks of overreliance, automation bias, deskilling, and diffusion of responsibility. The article organizes the literature into themes of augmentation, conditions shaping reliance and resistance to algorithms, and emerging concerns about governance and ethics in AI-mediated marketing decisions. It concludes that outcomes depend on how collaboration is designed, highlighting the need for transparent systems, clear accountability, and investment in human capabilities to ensure that AI serves as a tool for augmentation rather than a source of managerial dependence. Future research directions are outlined to guide more responsible and effective deployment of AI in marketing practice.