Technology Acceptance in AI-Mediated Communication: A Systematic Literature Review
Main Article Content
This study investigates how AI is accepted within human communication, using the Technology Acceptance Model (TAM) as a guiding framework. While TAM has been widely applied in fields such as e-commerce and healthcare, its application in AI-mediated communication (AI-MC) remains limited. This research aims to synthesize current research, identify dominant variables, and examine conceptual and methodological gaps in TAM’s use within AI communication contexts. Specifically, it seeks to explore how TAM has been applied to explain user interaction with AI as a communicative agent, rather than merely as a functional tool. Methods: A Systematic Literature Review (SLR) was conducted using the PRISMA 2020, which ensured a transparent and structured review process. A total of 158 eligible articles published between 2015 and 2024 were analyzed using narrative synthesis and bibliometric mapping. The findings show that TAM’s core constructs perceived usefulness, perceived ease of use, and behavioral intention remain dominant but are often insufficient to explain the social, emotional, and ethical dimensions of AI as a communicative partner. The results highlight the growing importance of additional factors such as trust in AI, perceived agency, transparency, and emotional appropriateness. The review also reveals an over-reliance on quantitative methods, with limited integration of communication theory. Conclusion: As a result, a new conceptual framework is proposed that integrates TAM with human communication concepts, emphasizing co-constructed meaning, social presence, and ethical interaction. This study concludes that understanding AI acceptance in communication requires an interdisciplinary model that goes beyond technical functionality to consider human-AI relational dynamics.
Keywords:
technology acceptance model, communication, artificial intelligence, systematic literature review, PRISMA
Algouzi, S., & Alzubi, A. A. F. (2023). The Study of AI-Mediated Communication and Socio-Cultural Language-Related Variables: Gmail Reply Suggestions. Applied Artificial Intelligence, 37(1). https://doi.org/10.1080/08839514.2023.2175114
Alshurideh, M., Jdaitawi, A., Sukkari, L., Al-Gasaymeh, A., Alzoubi, H., Damra, Y., Yasin, S., Al Kurdi, B., & Alshurideh, H. (2024). Factors affecting ChatGPT use in education employing TAM: A Jordanian universities’ perspective. International Journal of Data and Network Science, 8, 1599–1606. https://doi.org/10.5267/j.ijdns.2024.3.007
Asif, M., & Gouqing, Z. (2024). Innovative application of artificial intelligence in a multi-dimensional communication research analysis: A critical review. Discover Artificial Intelligence, 4, 37. https://doi.org/10.1007/s44163-024-00134-3
Baroni, I., Re Calegari, G., Scandolari, D., & Celino, I. (2022). AI-TAM: a model to investigate user acceptance and collaborative intention in human-in-the-loop AI applications. Human Computation, 9(1), 1-21. https://doi.org/10.15346/hc.v9i1.134
Booth, A., Sutton, A., & Papaioannou, D. (2016). Systematic approaches to a successful literature review (2nd ed.). SAGE Publications.
Boucher, P. (2020). Artificial intelligence: How does it work, why does it matter, and what can we do about it? Scientific Foresight Unit (STOA), European Parliamentary Research Service. https://doi.org/10.2861/44572
Brock, J. K.-U., & Von Wangenheim, F. (2019). Demystifying AI: What digital transformation leaders can teach you about realistic artificial intelligence. California Management Review, 61(4), 110–134.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008
Gökçe, Y., Çavu?o?lu, S., Göral, M., Bayatkara, Y., Bükey, A., & Gökçe, F. (2024). A bibliometric analysis of the technology acceptance model and the use of robots in tourism studies. Worldwide Hospitality and Tourism Themes, 16(2), 178–189. https://doi.org/10.1108/WHATT-03-2024-0057
Gunawan, D., Putri, F. P., & Meidia, H. (2020). Bershca: Bringing chatbot into hotel industry in Indonesia. TELKOMNIKA Telecommunication, Computing, Electronics and Control, 18(2), 839–845. https://doi.org/10.12928/TELKOMNIKA.v18i2.14841
Guzman, A. L., & Lewis, S. C. (2020). Artificial intelligence and communication: A human–machine communication research agenda. New Media & Society, 22(1), 70–86. https://doi.org/10.1177/1461444819858691
Hancock, J. T., Naaman, M., & Levy, K. (2020). AI-mediated communication: Definition, research agenda, and ethical considerations. Journal of Computer-Mediated Communication, 25(1), 89–100. https://doi.org/10.1093/jcmc/zmz022
Hohenstein, J., & Jung, M. (2018). AI-supported messaging: An investigation of human–human text conversation with AI support. In CHI EA '18: Extended abstracts of the 2018 CHI conference on human factors in computing systems (pp. LBW089:1–LBW089:6). Association for Computing Machinery. https://doi.org/10.1145/3170427.3188699
Kim, S. D. (2024). Application and challenges of the Technology Acceptance Model in elderly healthcare: Insights from ChatGPT. Technologies, 12(5), 68. https://doi.org/10.3390/technologies12050068
Kleine, A. K., Kokje, E., Lermer, E., & Gaube, S. (2023). Attitudes toward the adoption of 2 artificial intelligence–enabled mental health tools among prospective psychotherapists: Cross-sectional study. JMIR Human Factors, 10, e46859. https://doi.org/10.2196/46859
Kumar, S., Verma, A. K., & Mirza, A. (2024). Digital transformation, artificial intelligence and society. Springer. Https://Link. Springer. Com/Book/10, 1007, 978–981.
Lavidas, K., Voulgari, I., Papadakis, S., Athanassopoulos, S., Anastasiou, A., Filippidi, A., Komis, V., & Karacapilidis, N. (2024). Determinants of humanities and social sciences students’ intentions to use artificial intelligence applications for academic purposes. Information, 15(6), 314. https://doi.org/10.3390/info15060314
Ma, J., Wang, P., Li, B., Wang, T., Pang, X. S., & Wang, D. (2024). Exploring user adoption of ChatGPT: A Technology Acceptance Model perspective. International Journal of Human–Computer Interaction, 41(2), 1431–1445. https://doi.org/10.1080/10447318.2024.2314358
Mieczkowski, H., Hancock, J. T., Naaman, M., Jung, M., & Hohenstein, J. (2021). AI-mediated communication: Language use and interpersonal effects in a referential communication task. Proceedings of the ACM on Human-Computer Interaction, 5(CSCW1), 1–14. https://doi.org/10.1145/3449091
Morreale, S. P., Spitzberg, B. H., & Barge, J. K. (2007). Human communication: Motivation, knowledge, and skills (2nd ed.). Thomson Wadsworth.
Ozili, P. K. (2024). Technology impact model: A transition from the technology acceptance model. AI & Society. https://doi.org/10.1007/s00146-024-01896-1
Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., ... & Moher, D. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ, 372, n71. https://doi.org/10.1136/bmj.n71
Pearson, J. C., Nelson, P. E., Titsworth, S., & Hosek, A. M. (2017). Human communication (6th ed.). McGraw-Hill Education.
Petticrew, M., & Roberts, H. (2006). Systematic reviews in the social sciences: A practical guide. Blackwell Publishing.
Puspitasari, I. W., Rinawan, F. R., Purnama, W. G., Susiarno, H., & Susanti, A. I. (2022). Development of a chatbot for pregnant women on a Posyandu application in Indonesia: From qualitative approach to decision tree method. Informatics, 9(4), 88. https://doi.org/10.3390/informatics9040088
Sarp, S. (2023). Artificial Intelligence in advertisements: A conceptual framework based on the technology acceptance model. Journal of Economics, Business and Organization Research, 5(2), 161-174.
Short, J., Williams, E., & Christie, B. (1976). The social psychology of telecommunications. John Wiley & Sons.
Thüs, D., Malone, S., & Brünken, R. (2024). Exploring generative AI in higher education: A RAG system to enhance student engagement with scientific literature. Frontiers in Psychology, 15, Article 1474892. https://doi.org/10.3389/fpsyg.2024.1474892
Towne, B. P. (2024). Exploring the complexities of AI-mediated communication and human-machine interaction. Yiwu Industrial & Commercial College.
Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the Technology Acceptance Model: Four longitudinal field studies. Management Science, 46(2), 186–204. https://doi.org/10.1287/mnsc.46.2.186.11926
Ye, T., Xue, J., He, M., Gu, J., Lin, H., Xu, B., & Cheng, Y. (2019). Psychosocial factors affecting artificial intelligence adoption in health care in China: Cross-sectional study. Journal of Medical Internet Research, 21(10), e14316. https://doi.org/10.2196/14316
Zhang, W., & Hou, Z. (2024). College teachers’ behavioral intention to adopt artificial intelligence-assisted teaching systems. IEEE Access, 12, 152812–152824. https://doi.org/10.1109/ACCESS.2024.3445909
Alshurideh, M., Jdaitawi, A., Sukkari, L., Al-Gasaymeh, A., Alzoubi, H., Damra, Y., Yasin, S., Al Kurdi, B., & Alshurideh, H. (2024). Factors affecting ChatGPT use in education employing TAM: A Jordanian universities’ perspective. International Journal of Data and Network Science, 8, 1599–1606. https://doi.org/10.5267/j.ijdns.2024.3.007
Asif, M., & Gouqing, Z. (2024). Innovative application of artificial intelligence in a multi-dimensional communication research analysis: A critical review. Discover Artificial Intelligence, 4, 37. https://doi.org/10.1007/s44163-024-00134-3
Baroni, I., Re Calegari, G., Scandolari, D., & Celino, I. (2022). AI-TAM: a model to investigate user acceptance and collaborative intention in human-in-the-loop AI applications. Human Computation, 9(1), 1-21. https://doi.org/10.15346/hc.v9i1.134
Booth, A., Sutton, A., & Papaioannou, D. (2016). Systematic approaches to a successful literature review (2nd ed.). SAGE Publications.
Boucher, P. (2020). Artificial intelligence: How does it work, why does it matter, and what can we do about it? Scientific Foresight Unit (STOA), European Parliamentary Research Service. https://doi.org/10.2861/44572
Brock, J. K.-U., & Von Wangenheim, F. (2019). Demystifying AI: What digital transformation leaders can teach you about realistic artificial intelligence. California Management Review, 61(4), 110–134.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008
Gökçe, Y., Çavu?o?lu, S., Göral, M., Bayatkara, Y., Bükey, A., & Gökçe, F. (2024). A bibliometric analysis of the technology acceptance model and the use of robots in tourism studies. Worldwide Hospitality and Tourism Themes, 16(2), 178–189. https://doi.org/10.1108/WHATT-03-2024-0057
Gunawan, D., Putri, F. P., & Meidia, H. (2020). Bershca: Bringing chatbot into hotel industry in Indonesia. TELKOMNIKA Telecommunication, Computing, Electronics and Control, 18(2), 839–845. https://doi.org/10.12928/TELKOMNIKA.v18i2.14841
Guzman, A. L., & Lewis, S. C. (2020). Artificial intelligence and communication: A human–machine communication research agenda. New Media & Society, 22(1), 70–86. https://doi.org/10.1177/1461444819858691
Hancock, J. T., Naaman, M., & Levy, K. (2020). AI-mediated communication: Definition, research agenda, and ethical considerations. Journal of Computer-Mediated Communication, 25(1), 89–100. https://doi.org/10.1093/jcmc/zmz022
Hohenstein, J., & Jung, M. (2018). AI-supported messaging: An investigation of human–human text conversation with AI support. In CHI EA '18: Extended abstracts of the 2018 CHI conference on human factors in computing systems (pp. LBW089:1–LBW089:6). Association for Computing Machinery. https://doi.org/10.1145/3170427.3188699
Kim, S. D. (2024). Application and challenges of the Technology Acceptance Model in elderly healthcare: Insights from ChatGPT. Technologies, 12(5), 68. https://doi.org/10.3390/technologies12050068
Kleine, A. K., Kokje, E., Lermer, E., & Gaube, S. (2023). Attitudes toward the adoption of 2 artificial intelligence–enabled mental health tools among prospective psychotherapists: Cross-sectional study. JMIR Human Factors, 10, e46859. https://doi.org/10.2196/46859
Kumar, S., Verma, A. K., & Mirza, A. (2024). Digital transformation, artificial intelligence and society. Springer. Https://Link. Springer. Com/Book/10, 1007, 978–981.
Lavidas, K., Voulgari, I., Papadakis, S., Athanassopoulos, S., Anastasiou, A., Filippidi, A., Komis, V., & Karacapilidis, N. (2024). Determinants of humanities and social sciences students’ intentions to use artificial intelligence applications for academic purposes. Information, 15(6), 314. https://doi.org/10.3390/info15060314
Ma, J., Wang, P., Li, B., Wang, T., Pang, X. S., & Wang, D. (2024). Exploring user adoption of ChatGPT: A Technology Acceptance Model perspective. International Journal of Human–Computer Interaction, 41(2), 1431–1445. https://doi.org/10.1080/10447318.2024.2314358
Mieczkowski, H., Hancock, J. T., Naaman, M., Jung, M., & Hohenstein, J. (2021). AI-mediated communication: Language use and interpersonal effects in a referential communication task. Proceedings of the ACM on Human-Computer Interaction, 5(CSCW1), 1–14. https://doi.org/10.1145/3449091
Morreale, S. P., Spitzberg, B. H., & Barge, J. K. (2007). Human communication: Motivation, knowledge, and skills (2nd ed.). Thomson Wadsworth.
Ozili, P. K. (2024). Technology impact model: A transition from the technology acceptance model. AI & Society. https://doi.org/10.1007/s00146-024-01896-1
Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., ... & Moher, D. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ, 372, n71. https://doi.org/10.1136/bmj.n71
Pearson, J. C., Nelson, P. E., Titsworth, S., & Hosek, A. M. (2017). Human communication (6th ed.). McGraw-Hill Education.
Petticrew, M., & Roberts, H. (2006). Systematic reviews in the social sciences: A practical guide. Blackwell Publishing.
Puspitasari, I. W., Rinawan, F. R., Purnama, W. G., Susiarno, H., & Susanti, A. I. (2022). Development of a chatbot for pregnant women on a Posyandu application in Indonesia: From qualitative approach to decision tree method. Informatics, 9(4), 88. https://doi.org/10.3390/informatics9040088
Sarp, S. (2023). Artificial Intelligence in advertisements: A conceptual framework based on the technology acceptance model. Journal of Economics, Business and Organization Research, 5(2), 161-174.
Short, J., Williams, E., & Christie, B. (1976). The social psychology of telecommunications. John Wiley & Sons.
Thüs, D., Malone, S., & Brünken, R. (2024). Exploring generative AI in higher education: A RAG system to enhance student engagement with scientific literature. Frontiers in Psychology, 15, Article 1474892. https://doi.org/10.3389/fpsyg.2024.1474892
Towne, B. P. (2024). Exploring the complexities of AI-mediated communication and human-machine interaction. Yiwu Industrial & Commercial College.
Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the Technology Acceptance Model: Four longitudinal field studies. Management Science, 46(2), 186–204. https://doi.org/10.1287/mnsc.46.2.186.11926
Ye, T., Xue, J., He, M., Gu, J., Lin, H., Xu, B., & Cheng, Y. (2019). Psychosocial factors affecting artificial intelligence adoption in health care in China: Cross-sectional study. Journal of Medical Internet Research, 21(10), e14316. https://doi.org/10.2196/14316
Zhang, W., & Hou, Z. (2024). College teachers’ behavioral intention to adopt artificial intelligence-assisted teaching systems. IEEE Access, 12, 152812–152824. https://doi.org/10.1109/ACCESS.2024.3445909
