Faktor Psikologis yang Mempengaruhi Penerimaan Teknologi AI dalam Bisnis Digital (Kajian Literatur)

Tetty Winda  Siregar

doi:10.31004/riggs.v4i4.3558

Authors

Tetty Winda Siregar Universitas Gunadarma

DOI:

https://doi.org/10.31004/riggs.v4i4.3558

Keywords:

Artificial Intelligence, Penerimaan Teknologi, Faktor Psikologis, Trust, Technology Anxiety, Perceived Usefulness, Persepsi Risiko

Abstract

Penelitian ini bertujuan untuk mengidentifikasi dan menganalisis faktor-faktor psikologis yang memengaruhi penerimaan teknologi Artificial Intelligence (AI) dalam bisnis digital melalui pendekatan kajian literatur sistematis. Sebanyak 56 artikel terindeks internasional ditelaah untuk memperoleh pemahaman komprehensif mengenai variabel psikologis yang berperan dalam membentuk sikap dan perilaku pengguna terhadap teknologi AI. Hasil kajian menunjukkan bahwa kepercayaan (trust) merupakan faktor paling dominan yang mendorong penerimaan, terutama ketika sistem AI dinilai transparan, akurat, dan mampu memberikan penjelasan yang dapat dipahami. Sebaliknya, persepsi risiko dan kecemasan teknologi terbukti menjadi penghambat signifikan yang menurunkan intensi penggunaan, khususnya dalam konteks layanan digital yang membutuhkan keamanan dan akurasi tinggi. Faktor kognitif seperti perceived usefulness dan perceived ease of use tetap relevan, namun pada teknologi AI kedua variabel ini sangat dipengaruhi oleh konsistensi algoritma dan kemudahan sistem dalam menyampaikan informasi. Literasi AI juga menjadi faktor penting yang memediasi hubungan antara pemahaman teknologi dan kesiapan psikologis pengguna. Selain itu, norma sosial, dukungan organisasi, serta pengalaman interaksi manusia–AI turut memengaruhi penerimaan secara signifikan. Temuan penelitian ini menekankan pentingnya pendekatan multidisipliner yang menggabungkan aspek psikologis, sosial, dan teknis guna mengoptimalkan implementasi AI dalam bisnis digital, serta membuka peluang bagi penelitian lanjutan yang mengeksplorasi dinamika penerimaan AI dalam konteks industri yang berbeda.

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References

Afroogh, S., Akbari, A., Malone, E., Kargar, M., & Alambeigi, H. (2024). Trust in AI: progress, challenges, and future directions. Humanities and Social Sciences Communications, 11(1), 1–30.

Aini, S. (2025). Trusting AI in Finance: The Role of Psychological Traits and AI Literacy in Shaping User Behaviour Toward Robo-Advisors. The South East Asian Journal of Management, 19(2), 4.

Bach, T. A., Khan, A., Hallock, H., Beltrão, G., & Sousa, S. (2024). A systematic literature review of user trust in AI-enabled systems: An HCI perspective. International Journal of Human–Computer Interaction, 40(5), 1251–1266.

Choung, H., David, P., & Ross, A. (2023). Trust in AI and its role in the acceptance of AI technologies. International Journal of Human–Computer Interaction, 39(9), 1727–1739.

Constantinides, P., Henfridsson, O., & Parker, G. G. (2018). Introduction—platforms and infrastructures in the digital age. In Information systems research (Vol. 29, Issue 2, pp. 381–400). Informs.

Dietvorst, B. J., Simmons, J. P., & Massey, C. (2015). Algorithm aversion: people erroneously avoid algorithms after seeing them err. Journal of Experimental Psychology: General, 144(1), 114.

Dwivedi, Y. K., Kshetri, N., Hughes, L., Slade, E. L., Jeyaraj, A., Kar, A. K., Baabdullah, A. M., Koohang, A., Raghavan, V., & Ahuja, M. (2023). Opinion Paper:“So what if ChatGPT wrote it?” Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy. International Journal of Information Management, 71, 102642.

Ismatullaev, U. V. U., & Kim, S.-H. (2024). Review of the factors affecting acceptance of AI-infused systems. Human Factors, 66(1), 126–144.

Kelly, S., Kaye, S.-A., & Oviedo-Trespalacios, O. (2023). What factors contribute to the acceptance of artificial intelligence? A systematic review. Telematics and Informatics, 77, 101925.

Khanfar, A. A., Kiani Mavi, R., Iranmanesh, M., & Gengatharen, D. (2024). Determinants of artificial intelligence adoption: research themes and future directions. Information Technology and Management, 1–21.

Lee, A. T., Ramasamy, R. K., & Subbarao, A. (2025). Understanding psychosocial barriers to healthcare technology adoption: A review of TAM technology acceptance model and unified theory of acceptance and use of technology and UTAUT frameworks. Healthcare, 13(3), 250.

Lu, X., Vijaykumar, S., Jin, Y., & Rogerson, D. (2022). Think before you Share: Beliefs and emotions that shaped COVID-19 (Mis) information vetting and sharing intentions among WhatsApp users in the United Kingdom. Telematics and Informatics, 67, 101750.

Symasek, L., Yeazitzis, T., Weger, K., & Mesmer, B. (2025). Recent developments in individual difference research to inform the adoption of AI technology. Systems, 13(3), 156.

Venkatesh, V., Thong, J. Y. L., & Xu, X. (2016). Unified theory of acceptance and use of technology: A synthesis and the road ahead. Journal of the Association for Information Systems, 17(5), 328–376.

Wirtz, J. , Zeithaml, V., Gistri, G., & Soscia, I. (2023). How AI shapes customer experience and customer trust: A systematic review. . Journal of Service Management, 34(2), 145–169.

Zhou, Q., Yang, L., Tang, Y., Yang, J., Zhou, W., Guan, W., Yan, L., & Liu, Y. (2025). The mediation of trust on artificial intelligence anxiety and continuous adoption of artificial intelligence technology among primacy nurses: a cross-sectional study. BMC Nursing, 24(1), 724.