What Are the Factors That Drive AI Acceptance: A Meta-Analysis Approach

Antecedents of technology acceptance (TA) are known to be positively associated with measures such as usage intention, behavioral intention, attitude, and satisfaction. Although technology acceptance is investigated widely in prior research, it is not currently clear which variables or factors drive technology acceptance and under different service contexts or conditions. To examine the strength these effects in the artificial intelligence literature, we adopt a meta-analysis approach. We have scoped the literature on artificial intelligence, acceptance measures, and factors affecting acceptance in extant literature. We narrowed our search to business context to find AI-based tools that users, consumers, and customers interact with transactionally, such as chatbots. Findings show AI-based technology factors affect acceptance differently in various service industry contexts as preliminary results. These results have critical implications for researchers and practitioners studying which type of AI-based technology strengthen consumers use in different service contexts. These preliminary findings will be extended to look at interactive relationships of factors affecting acceptance in different contexts.