Abstract
This study examined how consumer awareness of algorithmic risks, perceived usefulness, and trust in Artificial Intelligence (AI) and Machine Learning (ML) developers are associated with intentions to adopt AI/ML applications. Using a 32-item quantitative survey of 115 recent AI/ML users, the research found that while risk awareness and trust are correlated with adoption intentions, only perceived usefulness is uniquely associated with adoption when all factors are considered together. Risk and trust are associated with adoption in part through their relationships with perceptions of usefulness, rather than as independent barriers. These results highlight the importance of transparent risk communication, ethical development, and clear demonstrations of utility to support AI adoption. Overall, AI adoption intentions appear to align most strongly with users perceiving clear benefits, alongside trust and perceptions of effective risk management.