  Generative AI has ushered in the ability to generate content that closely
mimics human contributions, introducing an unprecedented threat: Deployed en
masse, these models can be used to manipulate public opinion and distort
perceptions, resulting in a decline in trust towards digital platforms. This
study contributes to marketing literature and practice in three ways. First, it
demonstrates the proficiency of AI in fabricating disinformative user-generated
content (UGC) that mimics the form of authentic content. Second, it quantifies
the disruptive impact of such UGC on marketing research, highlighting the
susceptibility of analytics frameworks to even minimal levels of
disinformation. Third, it proposes and evaluates advanced detection frameworks,
revealing that standard techniques are insufficient for filtering out
AI-generated disinformation. We advocate for a comprehensive approach to
safeguarding marketing research that integrates advanced algorithmic solutions,
enhanced human oversight, and a reevaluation of regulatory and ethical
frameworks. Our study seeks to serve as a catalyst, providing a foundation for
future research and policy-making aimed at navigating the intricate challenges
at the nexus of technology, ethics, and marketing.
