<p>Products developed through human-artificial intelligence collaboration (HAIC) are emerging in high-stakes domains, such as pharmaceuticals, where failure can lead to harm. These products contain information asymmetries and tensions in agency configuration, whether the process is AI- or human-dominant. The information systems (IS) literature has few studies examining consumer acceptance of these products through the lens of transparency, social acceptance, and agency configuration. In response, this study explores two research questions: (1) How does the transparency in the HAIC process and the social value of the HAIC-developed product shape consumers’ trust and acceptance? and (2) How does the agency configuration affect the relationship between social value and consumers’ trust and acceptance? These questions are grounded in a conceptual model drawing on signaling theory and the theory of consumption values to examine consumer acceptance of HAIC-developed products in high-stakes domains, such as pharmaceuticals. The study employs an experimental design with simulated packaging disclosures of agency configuration (AI-dominant vs. human-dominant) for an over-the-counter medicine. It uses partial least squares structural equation modeling (PLS-SEM) to analyze the data (n1 = 262 and n2 = 238 consumers in the AI-dominant and human-dominant conditions, respectively). The findings reveal that transparency in the HAIC process increases trust in both conditions but enhances social value only in the human-dominant condition. Social value increases trust and acceptance, with these effects being stronger in the AI-dominant configuration. The study advances IS research by offering guidance on building consumer trust and acceptance through the disclosure of internal decisions about HAIC processes.</p>