The Technology Acceptance Model (TAM) is the key model in understanding predictors of human behavior towards potential acceptance or rejection of a technology (Granić and Marangunić (2019). The TAM predicts how likely someone is to utilize a given technology based on two factors: perceived utility and perceived ease of use (Sagnier et al, 2020). Perceived usefulness is defined as the degree to which a person believes that adopting a specific system will increase his or her job performance whereas, perceived ease of use refers to a person’s belief that using a specific system will need little effort (Sagnier et al, 2020). The rapid growth of artificial intelligence (AI) technology has prompted the development of AI-based intelligent products. Recent advancements in computing capabilities have brought about rapid growth in artificial intelligence (AI) technologies such as natural language processing, voice recognition, and machine learning. (Sagnier et al., 2020). Sohn and Kwon (2020) state that if users have a positive opinion of the attributes of a technology as they use it, they will consider the technology easy to use. Users of AII-based intelligent products such as the Amazon Echo has an impact on daily life and is considered easy to use (Sohn and Kwon. 2020). Amazon has a market advantage because of its pioneer status in the smart speaker market, and consumers appreciate the ease of use of Amazon Echo, which connects more than 12,000 devices of 2000 brands (Sohn and Kwon. 2020).
Granić, A., & Marangunić, N. (2019). Technology acceptance model in educational context: A systematic literature review. British Journal of Educational Technology, 50(5), 2572–2593. doi-org.lopes.idm.oclc.org/10.1111/bjet.12864
Sagnier, C., Loup-Escande, E., Lourdeaux, D., Thouvenin, I., & Valléry, G. (2020). User Acceptance of Virtual Reality: An Extended Technology Acceptance Model. International Journal of Human–Computer Interaction, 36(11), 993–1007. doi.org/10.1080/10447318.2019.1708612
Sohn, K., & Kwon, O. (2020). Technology acceptance theories and factors influencing artificial Intelligence-based intelligent products. Telematics and Informatics, 47. doi-org.lopes.idm.oclc.org/10.1016/j.tele.2019.101324
