Perspektif Gen Z sebagai Digital Savvy terhadap niat untuk menggunakan AI di tempat kerja
Abstract
Abstrak : Generasi Z tumbuh di era digital yang mapan dan dikenal mahir teknologi, serta memiliki pandangan positif tentang AI. Namun adanya kekhawatiran dan rasa tidak nyaman terhadap teknologi AI dapat mempengaruhi niat untuk menggunakan AI secara berkelanjutan. Penelitian ini bertujuan untuk mengkaji dan mengidentifikasi pengaruh General Attitudes towards Artificial Intelligence Scale (GAAIS) terhadap Continuance Intention (CI) pada Generasi Z di tempat kerja. Teori Perilaku Terencana (Theory of Planned Behaviour/ TPB) menjadi landasan teoretis penelitian ini, dengan fokus pada sikap (attitude) sebagai variabel independen. Data dikumpulkan melalui kuesioner dari 119 responden yang terdiri dari Generasi X, Milenial, dan Z, serta wawancara dari 5 responden generasi Z yang aktif bekerja serta mahir menggunakan AI. Hasil analisis menunjukkan bahwa GAAIS berpengaruh signifikan terhadap CI pada Generasi Z. Temuan ini mengindikasikan bahwa sikap terhadap AI memengaruhi niat Generasi Z untuk terus menggunakan teknologi AI di masa depan. Penelitian ini memberikan wawasan mengenai bagaimana AI dapat dimanfaatkan secara efektif di lingkungan kerja untuk meningkatkan efisiensi dan produktivitas.
Kata Kunci : Artificial Intelligence, Digital Savvy, Generation Z, Continuous Intention, General Attitudes toward Artificial Intelligence Scale
Downloads
References
Ashfaq, M. et al. (2020) ‘I, Chatbot: Modeling the determinants of users’ satisfaction and continuance intention of AI-powered service agents’, Telematics and Informatics, 54(July), p. 101473. doi: 10.1016/j.tele.2020.101473
Baskoro, G., Mariza, I. and Sutapa, I. N. (2023) ‘Innovation to Improve Critical Thinking Skills in the Generation Z using Peeragogy as a Learning Approach and Artificial Intelligence (AI) as a Tool’, Jurnal Teknik Industri, 25(2), pp. 121–130. doi: 10.9744/jti.25.2.121-130.
Ghozali, (2009), Aplikasi Analisis dengan program SPSS. Universitas Dipenogoro. Semarang
Jelahut, F. E. (2023) ‘Chat Gpt Artificial Intelligence: Phenomenology Studies Among Generation Z Students’, Mediakom : Jurnal Ilmu Komunikasi, 7(2), pp. 170–176. doi: 10.35760/mkm.2023.v7i2.9580.
Kandoth, S. and Shekhar, S. K. (2017) ‘Alternative evaluation of S&P 500 index in relation to quantitative easing’, Forum Scientiae Oeconomia, 5(1), pp. 5–18. doi: 10.23762/fso.
Mahasneh, R. et al. (2023) ‘Increasing employer willingness to hire people with disability: the perspective of disability employment service providers’, Journal of Social Marketing, 13(3), pp. 361–379. doi: 10.1108/JSOCM-08-2022-0174.
Maria Pangkey, F., Furkan, L. M. and Edy Herman, L. (2020) ‘Exploring the impact of Artiicial Intelligence and Digital Marketing on Intention to Use Online Transportation: a Lesson Learned from Indonesian Millenials Exploring the impact of Artificial Intelligence and Digital Marketing on Intention to Use Online Tr’.
Muhtar, 2023. Mengenal 6 Macam Generasi di Indonesia Sesuai Tahun Lahir, Kamu Termasuk yang Mana?. Retrieved May 28, 2024 from https://uici.ac.id/mengenal-6-macam-generasi-di-indonesia-sesuai-tahun-lahir-kamu-termasuk-yang-mana/.
Nedelko, Z., Potocan, V. and Dabić, M. (2015) ‘Current and future use of management tools’, E a M: Ekonomie a Management, 18(1), pp. 28–45. doi: 10.15240/tul/001/2015-1-003.
Nguyen, T. M., Dinh, V. T. and Nham, P. T. (2019) ‘Online knowledge sharing in Vietnamese telecommunication companies: An integration of social psychology models’, Knowledge Management and E-Learning, 11(4), pp. 497–521. doi: 10.34105/j.kmel.2019.11.026.
Pereira, T. et al. (2022) ‘New Insights into Consumers’ Intention to Continue Using Chatbots in the Tourism Context’, Journal of Quality Assurance in Hospitality and Tourism, 00(00), pp. 1–27. doi: 10.1080/1528008X.2022.2136817.
Purba, Djuli Sjafei : Pelatihan Penggunaan Software SPSS Dalam Pengolahan Regressi Linear Berganda Untuk Mahasiswa Fakultas Ekonomi Universitas Simalungun Di Masa Pandemi Covid 19
Rauf, A. et al. (2022) ‘Millennials’ perceptions of artificial intelligence in hotel service encounters’, Consumer Behavior in Tourism and Hospitality, 17(1), pp. 3–16. doi: 10.1108/CBTH-04-2021-0104.
Reinke, K. and Gerlach, G. I. (2022) ‘Linking Availability Expectations, Bidirectional Boundary Management Behavior and Preferences, and Employee Well-Being: an Integrative Study Approach’, Journal of Business and Psychology, 37(4), pp. 695–715. doi: 10.1007/s10869-021-09768-x
Rumawas, W. (2022) ‘Employees’ Turnover Intention in the Construction Industry in Indonesia’, Journal of Construction in Developing Countries, 27(2), pp. 127–146. doi: 10.21315/jcdc-03-21-0050.
Schepman, A. and Rodway, P. (2023) ‘The General Attitudes towards Artificial Intelligence Scale (GAAIS): Confirmatory Validation and Associations with Personality, Corporate Distrust, and General Trust’, International Journal of Human-Computer Interaction, 39(13), pp. 2724–2741. doi: 10.1080/10447318.2022.2085400.
Sudiana, I. W. et al. (2022) ‘Reflection on Values of Financial Governance of Village Credit Institutions in Bali’, Quality - Access to Success, 23(186), pp. 269–274. doi: 10.47750/QAS/23.186.35.
Talentics, 2023. Artificial Intelligence: Contoh Penggunaan AI di Bidang HR. Retrieved May,2024 from https://talentics.id/resources/blog/artificial-intelligence-contoh-pengguna
an-ai-di-bidang-hr/
Waleed, M., Bashir, F. and Nasim, I. (2023) ‘Artificial Intelligence Revolution: Shaping the Future of Millennials’, … of Humanities and Social …, 11(04), pp. 4261–4274. doi: 10.52131/pjhss.2023.1104.0689.
