Main Article Content
Abstract
This study analyzes how public digital artifacts relevant to the context of business students frame the use of generative AI in investment and budgeting decisions, how trust and risk perceptions toward AI outputs are represented, and how norms of use are displayed in the digital ecology. The study uses a qualitative approach through a thematic-interpretive analysis of public digital artifacts from TikTok, X, Threads, YouTube, and Stockbit during January 2025–February 2026. The final analytical corpus consists of 44 selected public entries, which include 39 cross-platform primary digital artifacts and 5 contextually reinforcing sources of limited use. The discussion of the themes relies primarily on primary artifacts on YouTube, X, and Stockbit, while TikTok and Threads are used primarily to clarify the digital norm ecology. The analysis yields four main patterns: AI is interpreted as a financial co-pilot ; trust in AI is selective and contextual; verification and affirmation of human judgment become norms of use; and digital spaces play a role in both normalizing and limiting the use of AI. These findings suggest that financial behavior in the context of business students in the AI era is more appropriately understood as a digital representation shaped by the interaction between economic rationality, calibration of trust in technology, and digital communication culture
Keywords
Article Details

This work is licensed under a Creative Commons Attribution 4.0 International License.
References
- Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211. https://doi.org/10.1016/0749-5978(91)90020-T
- Al-Okaily, M. (2025). ChatGPT as an educational resource for accounting students: Expanding the classical TAM model. Education and Information Technologies, 30, 16671–16685. https://doi.org/10.1007/s10639-025-13391-1
- Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101. https://doi.org/10.1191/1478088706qp063oa
- Eysenbach, G., & Till, J. E. (2001). Ethical issues in qualitative research on internet communities. BMJ, 323(7321), 1103–1105. https://doi.org/10.1136/bmj.323.7321.1103
- Han, J.-H., & Ko, D. (2025). Trust formation, error impact, and repair in human–AI financial advisory: A dynamic behavioral analysis. Behavioral Sciences, 15(10), Article 1370. https://doi.org/10.3390/bs15101370
- Herawati, N. T., Candiasa, I. M., Yadnyana, I. K., & Suharsono, N. (2018). Factors that influence financial behavior among accounting students in Bali. International Journal of Business Administration, 9(3), 30–38. https://doi.org/10.5430/ijba.v9n3p30
- Hermawan, M. D. A., & Septiani, D. (2024). Literasi keuangan dan dampaknya terhadap perilaku keuangan mahasiswa: Tinjauan literatur. Jurnal STIE Semarang, 16(3), 188–196. https://doi.org/10.33747/stiesmg.v16i3.762
- Hirshleifer, D. (2001). Investor psychology and asset pricing. The Journal of Finance, 56(4), 1533–1597. https://doi.org/10.1111/0022-1082.00379
- Klingbeil, A., Grützner, C., & Schreck, P. (2024). Trust and reliance on AI—An experimental study on the extent and costs of overreliance on AI. Computers in Human Behavior, 160, Article 108352. https://doi.org/10.1016/j.chb.2024.108352
- Kong, Y., Nie, Y., Dong, X., Mulvey, J. M., Poor, H. V., Wen, Q., & Zohren, S. (2024). Large language models for financial and investment management: Applications and benchmarks. The Journal of Portfolio Management, 51(2), 162–181. https://doi.org/10.3905/jpm.2024.1.645
- Lusardi, A., & Mitchell, O. S. (2011). Financial literacy around the world: An overview. Journal of Pension Economics & Finance, 10(4), 497–508. https://doi.org/10.1017/S1474747211000448
- Maruszewska, E. W., Ziemba, E. W., Grabara, D., & Renik, K. (2024). The determinants of ChatGPT usage among accounting students: The role of habit, social influence, and facilitating conditions. Zeszyty Teoretyczne Rachunkowości, 48(3), 215–232. https://doi.org/10.5604/01.3001.0054.7264
- Nie, Y., Kong, Y., Dong, X., Mulvey, J. M., Poor, H. V., Wen, Q., & Zohren, S. (2023). Large language models in finance: A survey. In Proceedings of the 4th ACM International Conference on AI in Finance (pp. 374–382). Association for Computing Machinery. https://doi.org/10.1145/3604237.3626869
- Nowell, L. S., Norris, J. M., White, D. E., & Moules, N. J. (2017). Thematic analysis: Striving to meet the trustworthiness criteria. International Journal of Qualitative Methods, 16, 1–13. https://doi.org/10.1177/1609406917733847
- Pak, T.-Y. (2026). How individuals use generative AI for personal financial management. Journal of Behavioral and Experimental Finance. Advance online publication. https://doi.org/10.1016/j.jbef.2026.101145
- Polyportis, A., & Pahos, N. (2025). Understanding students’ adoption of the ChatGPT chatbot in higher education: The role of anthropomorphism, trust, design novelty and institutional policy. Behaviour & Information Technology, 44(2), 315–336. https://doi.org/10.1080/0144929X.2024.2317364
- Pradiningtyas, T. E., & Lukiastuti, F. (2019). Pengaruh pengetahuan keuangan dan sikap keuangan terhadap locus of control dan perilaku pengelolaan keuangan mahasiswa ekonomi. Jurnal Minds: Manajemen Ide dan Inspirasi, 6(1), 96–112. https://doi.org/10.24252/minds.v6i1.9274
- Rasool, N., & Ullah, S. (2020). Financial literacy and behavioural biases of individual investors: Empirical evidence of Pakistan Stock Exchange. Journal of Economics, Finance and Administrative Science, 25(50), 261–278. https://doi.org/10.1108/JEFAS-03-2019-0031
- Ritakumalasari, N., & Susanti, A. (2021). Literasi keuangan, gaya hidup, locus of control, dan parental income terhadap perilaku keuangan mahasiswa. Jurnal Ilmu Manajemen, 9(4), 1440–1450. https://doi.org/10.26740/jim.v9n4.p1440-1450
- Sundkvist, C. H., & Kulset, E. M. (2024). Teaching accounting in the era of ChatGPT—The student perspective. Journal of Accounting Education, 69, Article 100932. https://doi.org/10.1016/j.jaccedu.2024.100932
- Tan, X., Xiao, J. J., Meng, K., & Xu, J. (2025). Financial education and budgeting behavior among college students: Extending the theory of planned behavior. International Journal of Bank Marketing, 43(3), 506–521. https://doi.org/10.1108/IJBM-05-2024-0285
- Ziemba, E. W., Maruszewska, E. W., Grabara, D., & Renik, K. (2024). Acceptance and use of ChatGPT among accounting and finance higher education students. In M. Hernes & J. Wątróbski (Eds.), Emerging challenges in intelligent management information systems (pp. 185–202). Springer. https://doi.org/10.1007/978-3-031-66761-9_16
References
Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211. https://doi.org/10.1016/0749-5978(91)90020-T
Al-Okaily, M. (2025). ChatGPT as an educational resource for accounting students: Expanding the classical TAM model. Education and Information Technologies, 30, 16671–16685. https://doi.org/10.1007/s10639-025-13391-1
Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101. https://doi.org/10.1191/1478088706qp063oa
Eysenbach, G., & Till, J. E. (2001). Ethical issues in qualitative research on internet communities. BMJ, 323(7321), 1103–1105. https://doi.org/10.1136/bmj.323.7321.1103
Han, J.-H., & Ko, D. (2025). Trust formation, error impact, and repair in human–AI financial advisory: A dynamic behavioral analysis. Behavioral Sciences, 15(10), Article 1370. https://doi.org/10.3390/bs15101370
Herawati, N. T., Candiasa, I. M., Yadnyana, I. K., & Suharsono, N. (2018). Factors that influence financial behavior among accounting students in Bali. International Journal of Business Administration, 9(3), 30–38. https://doi.org/10.5430/ijba.v9n3p30
Hermawan, M. D. A., & Septiani, D. (2024). Literasi keuangan dan dampaknya terhadap perilaku keuangan mahasiswa: Tinjauan literatur. Jurnal STIE Semarang, 16(3), 188–196. https://doi.org/10.33747/stiesmg.v16i3.762
Hirshleifer, D. (2001). Investor psychology and asset pricing. The Journal of Finance, 56(4), 1533–1597. https://doi.org/10.1111/0022-1082.00379
Klingbeil, A., Grützner, C., & Schreck, P. (2024). Trust and reliance on AI—An experimental study on the extent and costs of overreliance on AI. Computers in Human Behavior, 160, Article 108352. https://doi.org/10.1016/j.chb.2024.108352
Kong, Y., Nie, Y., Dong, X., Mulvey, J. M., Poor, H. V., Wen, Q., & Zohren, S. (2024). Large language models for financial and investment management: Applications and benchmarks. The Journal of Portfolio Management, 51(2), 162–181. https://doi.org/10.3905/jpm.2024.1.645
Lusardi, A., & Mitchell, O. S. (2011). Financial literacy around the world: An overview. Journal of Pension Economics & Finance, 10(4), 497–508. https://doi.org/10.1017/S1474747211000448
Maruszewska, E. W., Ziemba, E. W., Grabara, D., & Renik, K. (2024). The determinants of ChatGPT usage among accounting students: The role of habit, social influence, and facilitating conditions. Zeszyty Teoretyczne Rachunkowości, 48(3), 215–232. https://doi.org/10.5604/01.3001.0054.7264
Nie, Y., Kong, Y., Dong, X., Mulvey, J. M., Poor, H. V., Wen, Q., & Zohren, S. (2023). Large language models in finance: A survey. In Proceedings of the 4th ACM International Conference on AI in Finance (pp. 374–382). Association for Computing Machinery. https://doi.org/10.1145/3604237.3626869
Nowell, L. S., Norris, J. M., White, D. E., & Moules, N. J. (2017). Thematic analysis: Striving to meet the trustworthiness criteria. International Journal of Qualitative Methods, 16, 1–13. https://doi.org/10.1177/1609406917733847
Pak, T.-Y. (2026). How individuals use generative AI for personal financial management. Journal of Behavioral and Experimental Finance. Advance online publication. https://doi.org/10.1016/j.jbef.2026.101145
Polyportis, A., & Pahos, N. (2025). Understanding students’ adoption of the ChatGPT chatbot in higher education: The role of anthropomorphism, trust, design novelty and institutional policy. Behaviour & Information Technology, 44(2), 315–336. https://doi.org/10.1080/0144929X.2024.2317364
Pradiningtyas, T. E., & Lukiastuti, F. (2019). Pengaruh pengetahuan keuangan dan sikap keuangan terhadap locus of control dan perilaku pengelolaan keuangan mahasiswa ekonomi. Jurnal Minds: Manajemen Ide dan Inspirasi, 6(1), 96–112. https://doi.org/10.24252/minds.v6i1.9274
Rasool, N., & Ullah, S. (2020). Financial literacy and behavioural biases of individual investors: Empirical evidence of Pakistan Stock Exchange. Journal of Economics, Finance and Administrative Science, 25(50), 261–278. https://doi.org/10.1108/JEFAS-03-2019-0031
Ritakumalasari, N., & Susanti, A. (2021). Literasi keuangan, gaya hidup, locus of control, dan parental income terhadap perilaku keuangan mahasiswa. Jurnal Ilmu Manajemen, 9(4), 1440–1450. https://doi.org/10.26740/jim.v9n4.p1440-1450
Sundkvist, C. H., & Kulset, E. M. (2024). Teaching accounting in the era of ChatGPT—The student perspective. Journal of Accounting Education, 69, Article 100932. https://doi.org/10.1016/j.jaccedu.2024.100932
Tan, X., Xiao, J. J., Meng, K., & Xu, J. (2025). Financial education and budgeting behavior among college students: Extending the theory of planned behavior. International Journal of Bank Marketing, 43(3), 506–521. https://doi.org/10.1108/IJBM-05-2024-0285
Ziemba, E. W., Maruszewska, E. W., Grabara, D., & Renik, K. (2024). Acceptance and use of ChatGPT among accounting and finance higher education students. In M. Hernes & J. Wątróbski (Eds.), Emerging challenges in intelligent management information systems (pp. 185–202). Springer. https://doi.org/10.1007/978-3-031-66761-9_16