How do users adopt AI-generated content (AIGC)? An exploration of content cues and interactive cues

Abstract

Despite the growing adoption of AI-generated content (AIGC), its full potential remains underexplored. This study investigates the factors driving AIGC adoption and uncovers the psychological mechanisms underlying this process, grounded on the Information Adoption Model (IAM) integrated with the Cognition-Motivation-Emotion framework. Based on Structural Equation Modeling analysis, we find that AIGC adoption is shaped by content cues (perceived intelligence and anthropomorphism) and interactive cues (performance and effort expectancy), with emotions mediating the adoption process. This study enriches information processing literature by advancing IAM to accommodate the dynamic and iterative nature of AIGC adoption. It also establishes AIGC as a distinct category of digital content for the digital content adoption literature. Moreover, it shifts the focus of AI adoption research from technology adoption to content adoption.