Purpose This study examines individuals’ engagement with generative artificial intelligence (GenAI), which enables disinformation, and its effect on trust, perceptions and behaviors. It conceptualizes GenAI as a dual-use socio-technical system that facilitates and mitigates disinformation in digitally networked environments, with implications for organizations and society. Design/methodology/approach This study employs a theory-driven qualitative meta-synthesis approach of research. Through case-level coding and cross-study synthesis, it develops integrative insights into the role of GenAI in the evolving disinformation ecosystem. Findings Drawing on social information processing (SIP) theory, this study proposes an integrated framework that identifies the motivational drivers and technological affordances that enable individuals to generate, manipulate, and disseminate disinformation using GenAI. This framework demonstrates how GenAI’s analytical and cognitive capabilities can support disinformation detection and mitigation. Research limitations/implications This study advances our understanding by bridging fragmented perspectives across communication, psychology and information systems research. It integrates SIP theory, explains how cognitive biases influence credibility judgments in AI-mediated environments, and highlights GenAI’s potential to amplify structural inequalities. Practically, it outlines strategies for countering disinformation, including advanced detection tools, ethical governance, regulatory frameworks and media literacy initiatives, thus emphasizing the need for cross-sector collaboration. Originality/value This study provides a theoretically grounded synthesis of GenAI’s dual role in enabling and mitigating disinformation. This advances our understanding of how GenAI can be leveraged for positive societal impact amid rising information disorder.
Agarwal et al. (Wed,) studied this question.