The Role of Perceived Value on Adoption and Usage of Artificial Intelligence in Business

Purpose: This study explores the factors that influence the adoption and use of Artificial Intelligence (AI) in business, with a specific emphasis on the role of perceived value. It utilizes models such as the Technology Acceptance Model (TAM), the Unified Theory of Acceptance and Use of Technology (UTAUT), UTAUT2, and the Value-based Adoption Model (VAM) to examine how cognitive and contextual factors - like perceived usefulness, enjoyment, technical complexity, perceived fees, and perceived value - affect AI adoption and usage. Design/methodology/approach: The research employed a quantitative design, gathering 278 valid responses through an online survey. The reliability and validity of the data were assessed using methods such as Cronbach's Alpha, Exploratory Factor Analysis (EFA), Confirmatory Factor Analysis (CFA), and Structural Equation Modeling (SEM) to analyze the relationships among the key variables. Findings: The findings indicate that usefulness and enjoyment positively influence perceived value, which in turn directly affects the adoption and use of AI. In contrast, technical complexity has a negative impact on perceived value, while perceived fees do not show a significant effect. Research limitations/implications: While the study focused specifically on perceived value in relation to the adoption and use of AI in business, it makes a significant contribution to the theoretical foundations of technology acceptance and usage (e.g., TAM, UTAUT, UTAUT2, VAM, and related works). Originality/value: This study highlights that cognitive factors such as usefulness and enjoyment are vital in driving AI adoption, while technical complexity acts as a limiting factor. It provides theoretical insights and practical guidance for businesses aiming to enhance the adoption and implementation of AI technologies.