The Role of Generative AI in Developing Business Intelligence in the Era of Digital Transformation

Authors

  • Septiana Wulandari Author
  • Hoirul Umam Author

Keywords:

Generative AI, Business Intelligence, Digital Transformation, Data Analysis, and Decision-Making

Abstract

Advancements in digital technology are driving companies to utilize data as a basis for business decision-making. Business Intelligence (BI) transforms data into actionable information, while Generative Artificial Intelligence (Generative AI) enables users to interact with data using natural language. This study examines the role of Generative AI in supporting the development of Business Intelligence amidst digital transformation, as well as the benefits and challenges associated with implementing this technology. A qualitative approach was employed using a literature review method, analyzing relevant scientific journal articles and publications. The findings indicate that Generative AI facilitates information retrieval, simplifies database query creation, summarizes reports, and supports data analysis for business decision-making. However, its implementation faces challenges such as output accuracy, data quality, information security, and the risk of misinterpreting results. Therefore, the use of Generative AI in Business Intelligence requires robust data management, verification of analysis results, and human oversight. This study aims to provide insights into the opportunities and obstacles involved in leveraging Generative AI to build Business Intelligence systems effectively and ethically.

Downloads

Download data is not yet available.

References

[1] Yang, X.-Y. (2025). Peran Pengambilan Keputusan Berbasis Data dalam Transformasi Digital Perusahaan. Studi dalam Ilmu Sosial & Humaniora. https://doi.org/10.63593/sssh.2709-7862.2025.05.004.

[2] Putra, F. P. E., et al. (2025). Optimalisasi infrastruktur cloud networking melalui integrasi SDN, NFV, dan multi-cloud. Jurnal Informatika dan Teknologi Komputer (JITEK), 5(1). https://doi.org/10.55606/jitek.v5i1.6099.

[3] Tampubolon, H. (2026). Manajemen Berbasis Data: Transformasi Pengambilan Keputusan Organisasi di Era Digital. Oikonomia: Jurnal Ekonomi Manajemen dan Akuntansi. https://doi.org/10.61942/oikonomia.v3i3.611.

[4] Handra, T., Rizky, A., Siahaan, MM, Lase, SH, & Al-Farouqi, K. (2026). Implementasi Business Intelligence untuk Mendukung Pengambilan Keputusan Strategis Berbasis Data di Organisasi Digital. Jurnal Technomedia https://doi.org/10.33050/dw7zn772.

[5] Hossain, Q., Yasmin, F., Biswas, TR, & Asha, N. (2024). Integrasi Analisis Big Data dalam Sistem Informasi Manajemen untuk Kecerdasan Bisnis. Jurnal Studi Bisnis dan Manajemen Saudi. https://doi.org/10.36348/sjbms.2024.v09i09.002.

[6] Kusumo, A., Setiawan, R., & Fitria, D. (2026). Mengintegrasikan kecerdasan bisnis ke dalam sistem informasi eksekutif untuk dukungan pengambilan keputusan tingkat lanjut. JISTecS: Jurnal Sistem Informasi, Teknologi dan Keamanan. https://doi.org/10.65881/jistecs.v1i1.51.

[7] Ebule, A. (2025). Memanfaatkan Kecerdasan Buatan dalam Sistem Kecerdasan Bisnis untuk Analisis Prediktif. Jurnal Internasional Penelitian Ilmiah dan Manajemen (IJSRM). https://doi.org/10.18535/ijsrm/v13i01.ec02.

[8] Kalota, F. (2024). Pengantar tentang Kecerdasan Buatan Generatif. Ilmu Pendidikan. https://doi.org/10.3390/educsci14020172.

[9] Shi, Y., & Sun, L. (2024). Bagaimana AI Generatif Mengubah Jurnalisme: Pengembangan, Aplikasi, dan Etika. Jurnalisme dan Media. https://doi.org/10.3390/journalmedia5020039.

[10] Chu, S., & Liu, J. (2025). Berdasarkan arsitektur konvergen BERT-GPT-GNN: mesin pembangkit cerdas untuk kueri SQL kompleks dalam kecerdasan bisnis. Discover Artificial Intelligence, 5. https://doi.org/10.1007/s44163-025-00381-y.

[11] Suresh, A. (2026). Demokratisasi Data Melalui Auto-BI: Menggunakan AI Generatif untuk Analisis Mandiri. Jurnal Internasional untuk Penelitian Multidisiplin . https://doi.org/10.36948/ijfmr.2026.v08i01.67384.

[12] Naphade, D. (2025). Transformasi Analitik Layanan Mandiri dengan AI untuk Percepatan Kecerdasan Bisnis. Jurnal Internasional Penelitian Ilmiah dalam Ilmu Komputer, Teknik, dan Teknologi Informasi . https://doi.org/10.32628/cseit25112489.

[13] P, A., J, H., S., K., P., NC, K, N., & A, S. (2025). Insight Pro: Memanfaatkan AI Generatif untuk Konversi Bahasa Alami ke SQL dalam Analisis Bisnis. Prosiding Konferensi Internasional ke-4 tentang Teknologi Informasi, Inovasi Sipil, Sains, dan Manajemen, ICITSM 2025, 28-29 April 2025, Tiruchengode, Tamil Nadu, India, Bagian II . https://doi.org/10.4108/eai.28-4-2025.2358008.

[14] Iatsiuta, V., & Kobets, V. (2025). Transformasi Komunikasi Bisnis dengan Solusi Berbasis Teknologi Kecerdasan Buatan dengan Dukungan Pemrosesan Bahasa Alami. Sains dan Inovasi . https://doi.org/10.15407/scine21.05.126.

[15] Yadav, D., & Selvakumar, P. (2025). Membuat Wawasan Data Dapat Diakses – Meningkatkan Analisis Bisnis melalui AI Generatif. Konferensi Internasional ke-5 tentang Teknologi Listrik, Komputer, dan Energi (ICECET) 2025 , 1-7. https://doi.org/10.1109/icecet63943.2025.11472383.

[16] Fikardos, M., Lepenioti, K., Bousdekis, A., Apostolou, D., & Mentzas, G. (2026). AI generatif untuk analisis data otonom. Intel. sistem. Aplikasi, 29 , 200626. https://doi.org/10.1016/j.iswa.2026.200626.

[17] Liu, J., & Chu, S. (2025). Text2SQL Business Intelligence system based on retrieval-augmented generation (RAG). Engineering Reports, 7(6), e70249. https://doi.org/10.1002/eng2.70249.

[18] Busany, N., Hadar, E., Hadad, H., Rosenblum, G., Maszlanka, Z., Akhigbe, O., & Amyot, D. (2024). Mengotomatiskan Persyaratan Kecerdasan Bisnis dengan AI Generatif dan Pencarian Semantik. Konferensi Komputer, Perangkat Lunak, dan Aplikasi Tahunan IEEE ke-49 (COMPSAC) 2025 , 1891-1898. https://doi.org/10.48550/arxiv.2412.07668.

[19] Reddy, S. (2024). AI Generatif dalam perawatan kesehatan: jalur translasi yang diinformasikan oleh ilmu implementasi tentang aplikasi, integrasi, dan tata kelola. Ilmu Implementasi: IS, 19. https://doi.org/10.1186/s13012-024-01357-9.

[20] Christensen, J., Hansen, JM, & Wilson, P. (2024). Memahami peran dan dampak halusinasi Kecerdasan Buatan (AI) Generatif dalam proses pengambilan keputusan pariwisata konsumen. Isu Terkini dalam Pariwisata, 28 , 545 - 560. https://doi.org/10.1080/13683500.2023.2300032.

[21] Putra, F. P. E., et al. (2024). Analysis of phishing attack trends, impacts and prevention methods: Literature study. Brilliance: Research of Artificial Intelligence, 4(1). https://doi.org/10.47709/brilliance.v4i1.4357.

[22] Putra, F. P. E., et al. (2024). The evolution of quality education: Impacts and challenges of using open educational resources (OER) and open educational practices (OEP) in the conceive-design-implement-operate (CDIO) framework. TEM Journal, 13(1). https://doi.org/10.18421/TEM131-40.

[23] Li, Z., Yi, W., & Chen, J. (2026). Accuracy paradox: Addressing epistemic, manipulative, and societal risks of hallucination in AI governance. Computer Law & Security Review. https://doi.org/10.1016/j.clsr.2026.106311.

[24] Hiniduma, K., Byna, S., & Bez, J. (2024). Kesiapan Data untuk AI: Survei 360 Derajat. ACM Computing Surveys, 57, 1-39. https://doi.org/10.1145/3722214.

[25] Putra, F. P. E., et al. (2023). Privasi dan keamanan penerapan IoT dalam kehidupan sehari-hari: Tantangan dan implikasi. Jurnal Sistim Informasi dan Teknologi, 5(2). https://doi.org/10.37034/jsisfotek.v5i2.232.

[26] Amoo, OO (2024). MENINJAU IMPLIKASI ETIKA AI DALAM PROSES PENGAMBILAN KEPUTUSAN. Jurnal Internasional Riset Manajemen & Kewirausahaan. https://doi.org/10.51594/ijmer.v6i2.773.

[27] Putra, F. P. E., et al. (2024). Penggunaan teknologi blockchain dalam jaringan komputer untuk meningkatkan keamanan data. Jurnal Informatika dan Teknologi Komputer 5(1). https://doi.org/10.55606/jitek.v5i1.5768.

[28] Nikiforova, A., Lnenicka, M., Melin, U., Valle-Cruz, D., Gill, A., Casiano Flores, C., Sirait, E., Luterek, M., Dreyling, R., & Tesarova, B. (2025). Adopsi AI yang Bertanggung Jawab di Sektor Publik: Taksonomi Berpusat pada Data dari Tantangan Adopsi AI. ArXiv, abs/2510.09634. https://doi.org/10.48550/arxiv.2510.09634.

[29] Uddin, SMM, Nazmussakib, M., Mustafizur, M., Bakhsh, MM, Islam, MA, Saha, US, Akter, T., & Ahmed, MK (2026). Kecerdasan Bisnis Berbasis AI: Meningkatkan Pengambilan Keputusan melalui Analisis Prediktif dan Big Data. Jurnal Posthumanisme. https://doi.org/10.63332/joph.v6i3.4083.

[30] Desai, D., & Desai, A. (2025). Mengintegrasikan AI Generatif dalam Business Intelligence: Kerangka Kerja Praktis untuk Meningkatkan Analitik Tambahan. Jurnal Internasional Ilmu Matematika, Teknik, dan Manajemen. https://doi.org/10.33889/ijmems.2025.10.3.036.

[31] Marripudugala, M., & Mothi, S. (2025). Applications of Generative AI in Business Analytics: Transforming Decision-Making and Strategy. 2025 IEEE International Conference on Contemporary Computing and Communications (InC4), 1-6. https://doi.org/10.1109/inc465408.2025.11256227.

[32] Ni'mah, N. R., Larasati, A., Laksana, C., & Mohamad, E. (2024). Business Intelligence System Design Based on Performance Monitoring Dashboard Using Online Analytical Processing (OLAP) Method. Jurnal Ilmiah Teknik Industri. https://doi.org/10.23917/jiti.v23i02.6016.

[33] Gultom, I., Cynthia, E., & Saeed, A. H. (2024). Visualization and Analysis of Employee Performance Data Using a Power BI-based Business Intelligence Dashboard. Journal of Computer Science Artificial Intelligence and Communications. https://doi.org/10.62712/jocsaic.v1i2.19.

[34] Putra, F. P. E., et al. (2023). Pengembangan sistem informasi laboratorium terintegrasi sistem akademik menggunakan agile scrum. Jurnal Informasi dan Teknologi, 5(2). https://doi.org/10.37034/jidt.v5i2.367.

[35] Putra, F. P. E., et al. (2025). Designing an Information System for Student Admissions at SMAN 1 Pademawu Using the Waterfall Method. Brilliance: Research of Artificial Intelligence, 5(1). https://doi.org/10.47709/brilliance.v5i1.6508.

[36] Dwivedi, R., & Elluri, L. (2024). Exploring Generative Artificial Intelligence Research: A Bibliometric Analysis Approach. IEEE Access, 12, 119884-119902. https://doi.org/10.1109/access.2024.3450629.

[37] He, R., Cao, J., & Tan, T. (2025). Generative artificial intelligence: a historical perspective. National Science Review, 12. https://doi.org/10.1093/nsr/nwaf050.

[38] Busany, N., Hadar, E., Hadad, H., Rosenblum, G., Maszlanka, Z., Akhigbe, O., & Amyot, D. (2024). Automating Business Intelligence Requirements with Generative AI and Semantic Search. 2025 IEEE 49th Annual Computers, Software, and Applications Conference (COMPSAC), 1891-1898. https://doi.org/10.48550/arxiv.2412.07668.

[39] Tabassum, I., & Samreen, S. F. (2026). OptiWise: A Web Based AI-Driven Decision Intelligence System with Explainable AI For Business Data Analytics. International Journal of Engineering Research and Science & Technology. https://doi.org/10.62643/ijerst.2026.v22.n3.4118.

[40] Putra, F. P. E., et al. (2025). Peran VPN dalam menjaga privasi pengguna jaringan publik. Jurnal Informatika dan Teknologi Komputer (JITEK), 5(1). https://doi.org/10.55606/jitek.v5i1.5834.

[41] Putra, F. P. E., et al. (2025). Analisis kinerja jaringan 5G dalam meningkatkan konektivitas Internet of Things (IoT). Jurnal Informatika dan Teknologi Komputer (JITEK), 5(1). https://doi.org/10.55606/jitek.v5i1.5836.

[42] Autio, C., et al. (2024). Artificial intelligence risk management framework: Generative artificial intelligence profile (NIST AI 600-1). National Institute of Standards and Technology. https://doi.org/10.6028/NIST.AI.600-1.

[43] Sava, M., & Tucker, J. (2026). When AI Sounds Right but Is Statistically Wrong: A Concept Paper Introducing the SAVA Framework for Responsible Business Decision-Making. Business Management Research and Applications: A Cross-Disciplinary Journal. https://doi.org/10.54093/bmra.v5i2.12796.

[44] Putra, F. P. E., et al. (2023). Interaktif dan personalisasi: Peningkatan pembelajaran IoT di sekolah. Jurnal Sistem Informasi dan Teknologi, 5(2). https://doi.org/10.37034/jsisfotek.v5i2.236.

[45] Wang, X., & Zhang, Y. (2026). LLM-Driven Business Intelligence for Retail Digital Transformation. Journal of Organizational and End User Computing. https://doi.org/10.4018/joeuc.411214.

[46] Nusullapalli, S. S., & Vanaja, P. (2026). Generative AI for Automated Data Analytics: Transforming Decision Intelligence. International Scientific Journal of Engineering and Management. https://doi.org/10.55041/isjem06820.

[47] Ande, K., Gupta, S., Ohja, A., Shaturaev, J., & Mirzayev, B. (2025). Generative AI and Cloud Data Engineering for Business Intelligence. 2025 International Conference on Sustainability, Innovation & Technology (ICSIT), 1-5. https://doi.org/10.1109/icsit65336.2025.11295004.

[48] Modgil, S., Gupta, S., Kar, A., & Tuunanen, T. (2025). How could Generative AI support and add value to non-technology companies – A qualitative study. Technovation. https://doi.org/10.1016/j.technovation.2024.103124.

[49] Smith, G. K. (2025). Strategic Integration of Generative AI: Opportunities, Challenges, and Organizational Impacts. Law, Economics and Society. https://doi.org/10.30560/les.v1n1p156.

[50] Rana, N. P., Pillai, R., Sivathanu, B., & Malik, N. (2024). Assessing the nexus of Generative AI adoption, ethical considerations and organizational performance. Technovation. https://doi.org/10.1016/j.technovation.2024.103064.

Published

14-10-2026

How to Cite

The Role of Generative AI in Developing Business Intelligence in the Era of Digital Transformation. (2026). Karapan Network Journal : Journal Computer Technology and Mobile Ad Hoc Network, 2(04). https://ejournal.omahtabing.com/knj/article/view/762

Most read articles by the same author(s)