AI Search Visibility And Brand Trust Formation: A Conceptual Framework For Startups In The Indonesian Digital Market

Background. The rapid proliferation of artificial intelligence (AI)-mediated search environments has fundamentally restructured how consumers discover and evaluate brands in digital markets. Despite growing scholarly attention to AI as an operational marketing tool, a critical gap persists regarding its role as a brand trust-building signal — particularly for startups and unknown brands that lack established reputational capital. Aims. This paper addresses two interrelated gaps: the absence of a conceptual framework examining AI search visibility as a trust signal, and the neglect of startups as a distinct context in AI marketing research. Methods. Using a conceptual research design grounded in systematic literature synthesis, this paper integrates Trust Transfer Theory, Signaling Theory, and the Elaboration Likelihood Model to develop a conceptual framework that explains how AI search visibility shapes brand trust formation. Four theoretical propositions are developed: AI search visibility positively influences brand trust (P1); brand trust enhances purchase intention (P2) and recommendation intention (P3); and collectivist cultural orientation moderates the relationship between AI search visibility and trust (P4). Conclusion. The Indonesian digital market provides the contextual grounding, given its collectivist orientation, dynamic startup ecosystem, and rapidly growing AI adoption. Implementation. Findings offer theoretical extensions and practical implications for startup brand strategy in algorithm-mediated marketplaces.