The Impact of Artificial Intelligence on Profitability: Does Firm Size Become a Determining Factor?
Article Sidebar
Main Article Content
Abstract
Penelitian ini mengkaji hubungan antara pengungkapan Kecerdasan Buatan (AI) dan profitabilitas, serta menyelidiki apakah ukuran perusahaan memoderasi hubungan tersebut pada perusahaan perbankan yang terdaftar di Bursa Efek Indonesia (BEI) pada tahun 2024. Desain penelitian kausal kuantitatif digunakan dengan sampel purposif sebanyak 46 bank. Pengungkapan AI diukur melalui analisis konten laporan tahunan menggunakan indikator biner, di mana nilai 1 mewakili adanya pengungkapan implementasi terkait AI dan nilai 0 mewakili ketiadaan pengungkapan tersebut. Profitabilitas diukur menggunakan *Return on Equity* (ROE), sedangkan ukuran perusahaan diukur menggunakan logaritma natural dari total aset. Analisis Regresi Moderasi (MRA) dilakukan setelah melakukan *mean-centering* pada variabel-variabel yang digunakan untuk menyusun suku interaksi. Hasil regresi sederhana menunjukkan bahwa pengungkapan AI berhubungan positif dengan profitabilitas. Namun, setelah ukuran perusahaan dan suku interaksi dimasukkan ke dalam model lengkap, pengaruh langsung pengungkapan AI menjadi tidak signifikan secara statistik. Ukuran perusahaan memiliki pengaruh positif dan signifikan terhadap profitabilitas, sedangkan interaksi antara pengungkapan AI dan ukuran perusahaan tidak signifikan secara statistik. Model lengkap tersebut menjelaskan sekitar 58,8% variasi dalam ROE. Temuan ini mengindikasikan bahwa ukuran perusahaan berkontribusi secara langsung terhadap perbedaan profitabilitas bank namun tidak memoderasi hubungan antara pengungkapan AI dan profitabilitas secara signifikan. Hasil penelitian menyarankan agar bank tidak hanya berfokus pada keberadaan inisiatif terkait AI, tetapi juga pada integrasi efektif inisiatif tersebut ke dalam proses operasional, tata kelola data, dan aktivitas bisnis yang menghasilkan nilai.
Article Details
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
References
Balan, V. (2022). Cloud-based, data-driven artificial intelligence and machine learning financial planning and analysis visualization platform. US Patent 11,461,723. https://patents.google.com/patent/US11461723B2/en
Barney, J. (1991). Firm Reources ad Sustained Competitive Advantege. In Journal of Management (Vol. 17, Issue 1, pp. 99–120).
Breillat, R. (2020). Industrial artificial intelligence, internet of things smart devices, and big data-driven decision-making in digital-twin-based cyber-physical production systems. Economics, Management, and Financial Markets. https://www.ceeol.com/search/article-detail?id=845236
Brynjolfsson, E., & Mcafee, A. (2017). The business of artificial intelligence. Harvard Business Review, 7(1), 1–2.
Brynjolfsson, E., & McAfee, A. (2014). The second machine age: Work progress and prosperity in a time of brilliant technologies. WW Norton & company.
Cannas, R. (2023). Exploring digital transformation and dynamic capabilities in agrifood SMEs. Journal of Small Business Management. https://doi.org/10.1080/00472778.2020.1844494
Chatterjee, S., Chaudhuri, R., & Vrontis, D. (2022). AI and digitalization in relationship management: Impact of adopting AI-embedded CRM system. Journal of Business Research. https://www.sciencedirect.com/science/article/pii/S0148296322005719
Chen, L., Chen, P., & Lin, Z. (2020). Artificial intelligence in education: A review. IEEE Access, 8, 75264–75278.
Davenport, T. H., & Ronanki, R. (2018). Artificial intelligence for the real world. Harvard Business Review, 96(1), 108–116.
Dhewanto, W., Umbara, A. N., & Hanifan, R. (2023). Towards Policy Development of Entrepreneurial Ecosystem: A Review in Indonesia Financial Technology Sector. Proceedings of the 8th International Conference on Industrial and Business Engineering, 282–290. https://doi.org/10.1145/3568834.3568841
Dwivedi, Y. K., Ismagilova, E., Hughes, D. L., Carlson, J., Filieri, R., Jacobson, J., Jain, V., Karjaluoto, H., Kefi, H., Krishen, A. S., Kumar, V., Rahman, M. M., Raman, R., Rauschnabel, P. A., Rowley, J., Salo, J., Tran, G. A., & Wang, Y. (2021). Setting the future of digital and social media marketing research: Perspectives and research propositions. International Journal of Information Management, 59, 102168. https://doi.org/https://doi.org/10.1016/j.ijinfomgt.2020.102168
Farayola, O. A. (2024). Revolutionizing banking security: integrating artificial intelligence, blockchain, and business intelligence for enhanced cybersecurity. Finance & Accounting Research Journal, 6(4), 501–514.
Fares, O. H., Butt, I., & Lee, S. H. M. (2023). Utilization of artificial intelligence in the banking sector: A systematic literature review. Journal of Financial Services Marketing, 28(4), 835–852.
Guan, C., Mou, J., & Jiang, Z. (2020). Artificial intelligence innovation in education: A twenty-year data-driven historical analysis. In International Journal of Innovation Studies. Elsevier. https://www.sciencedirect.com/science/article/pii/S2096248720300369
Harahap, M. A. K., Wurarah, R. N., Fathurohman, A., Suroso, A., & Iskandar, Y. (2023). Globalization Substance And Industrial Revolution 4.0 And The Role Of Technological Innovation For Economic Development Towards Entrepreneurship. Jurnal Bisnisman : Riset Bisnis Dan Manajemen, 4(3), 37–51. https://doi.org/10.52005/bisnisman.v4i3.122
Hendrayati, H., Achyarsyah, M., Marimon, F., Hartono, U., & Putit, L. (2024). The Impact of Artificial Intelligence on Digital Marketing: Leveraging Potential in a Competitive Business Landscape. Emerging Science Journal.
Hilary, G., & McLean, D. (2023). Financial decision making: an overview. The Handbook of Financial Decision …. https://books.google.com/books?hl=en&lr=&id=0-_REAAAQBAJ&oi=fnd&pg=PA2&dq=%22data+driven%22+financial+management&ots=eLpGnf0xbr&sig=l4pRSJgqRiYzSRKvagpqCMA99sk
Huang, M.-H., & Rust, R. T. (2018). Artificial intelligence in service. Journal of Service Research, 21(2), 155–172.
Jarrahi, M. H. (2018). Artificial intelligence and the future of work: Human-AI symbiosis in organizational decision making. Business Horizons, 61(4), 577–586.
Khan, A. N., Jabeen, F., Mehmood, K., Soomro, M. A., & Bresciani, S. (2023). Paving the way for technological innovation through adoption of artificial intelligence in conservative industries. Journal of Business Research, 165, 114019.
Makridakis, S. (2017). The forthcoming Artificial Intelligence (AI) revolution: Its impact on society and firms. Futures, 90, 46–60.
Munfaredi, A., Sulaiman, N., AlKhatib, R., & Wadi, R. A. (2022). The Impact of Digitalization on Managerial Accounting Roles. Artificial Intelligence for Sustainable Finance and Sustainable Technology: Proceedings of ICGER 2021 1, 502–511.
Schumpeter, J. A. (1934). The theory of economic development: An inquiry into profits, capital, credit, interest, and the business cycle. Harvard University Press.
Sood, S., & Kim, A. (2023). The Golden Age of the Big Data Audit: Agile Practices and Innovations for E-Commerce, Post-Quantum Cryptography, Psychosocial Hazards, Artificial Intelligence Algorithm Audits, and Deepfakes. International Journal of Innovation and Economic Development, 9(2), 7–23. https://doi.org/10.18775/ijied.1849-7551-7020.2015.92.2001
Volini, E., Schwartz, J., Roy, I., Hauptmann, M., & ... (2019). Leading the social enterprise: Reinvent with a human focus. Deloitte Global Human …. https://www.voced.edu.au/content/ngv:83375