ARTIFICIAL INTELLIGENCE AND BIG DATA IN ENHANCING DECISION-MAKING EFFECTIVENESS: A SYSTEMATIC LITERATURE REVIEW
Main Article Content
Dara Anindya Putri Umagapi
Nuril Huda
Sopiah
Advances in digital technology have transformed the way organizations make decisions. Artificial Intelligence (AI) and Big Data Analytics (BDA) are now key foundations for improving the effectiveness of strategic and operational decisions. This study examines the contribution of AI and BDA to the effectiveness of organizational decision-making through a Systematic Literature Review approach with the PRISM protocol. A total of 20 articles from Scopus published in 2020–2025 were analyzed descriptively, thematically, and through content analysis. The results show that AI accelerates, directs, and improves decision fairness, while BDA strengthens data-driven accuracy and prediction. The integration of the two forms an adaptive and intelligent decision-making system. These findings emphasize the relevance of dynamic capability and absorptive capacity theories, as well as the importance of infrastructure readiness, analytical competency, and technology governance within organizations. This study contributes theoretically and provides strategic direction for organizations in the digital transformation process of their decision-making.
Adrian, C., Abdullah, R., Atan, R., & Jusoh, Y. Y. (2023). Conceptual model development of big data analytics implementation assessment effect on decision-making. International Journal of Interactive Multimedia and Artificial Intelligence, 5(1), 92–99. https://reunir.unir.net/bitstream/handle/123456789/12363/ijimai_5_1_13_pdf_81158.pdf?sequence=1&isAllowed=y
Alasmri, N., & Basahel, S. (2022). Linking artificial intelligence use to improved decision-making, individual and organizational outcomes. ResearchGate. https://www.researchgate.net/publication/363093231
Boell, S. K., & Cecez-Kecmanovic, D. (2015). On being ‘systematic’ in literature reviews. Formulating Research Methods for Information Systems, 48(2), 161–173. https://doi.org/10.1016/j.infoandorg.2014.11.001
Cao, G., Duan, Y., & Li, G. (2025). Linking business analytics to decision making effectiveness: A path model analysis. IEEE Transactions on Engineering Management, 62(4), 384–395. https://uobrep.openrepository.com/bitstream/handle/10547/560379/accepted%20IEEE-final.pdf?sequence=1&isAllowed=y
Carter, W., & Wynne, K. T. (2021). Integrating artificial intelligence into team decision-making: Toward a theory of AI–human team effectiveness. European Management Review. https://app.scholarai.io/paper?paper_id=DOI:10.1111/emre.12685&original_url=https%3A%2F%2Fonlinelibrary.wiley.com%2Fdoi%2Fabs%2F10.1111%2Femre.12685
Cohen, W. M., & Levinthal, D. A. (1990). Absorptive capacity: A new perspective on learning and innovation. Administrative Science Quarterly, 35(1), 128–152. https://doi.org/10.2307/2393553
Di Vaio, A., Hassan, R., & Alavoine, C. (2022). Data intelligence and analytics: A bibliometric analysis of human–Artificial intelligence in public sector decision-making effectiveness. Technological Forecasting and Social Change, 178, 121602. https://www.sciencedirect.com/science/article/pii/S004016252100634X
Farhi, F., Jeljeli, R., Mohsen, M., & Lagha, F. B. (2024). The influence of big data analytics on strategic decision-making—A quantitative study. IEEE Xplore. https://ieeexplore.ieee.org/abstract/document/10776131/
Ghaleb, M. M. S., & Mirzaliev, S. (2024). Production efficiency: Role of decision making factors, big data and predictive analytics. ORESTA: Online Research Journal, 10(1). http://oresta.org/menu-script/index.php/oresta/article/download/762/263
Ghasemaghaei, M., Ebrahimi, S., & Hassanein, K. (2023). Data analytics competency for improving firm decision making performance. International Journal of Information Management, 38(1), 1–12. https://www.sciencedirect.com/science/article/pii/S0963868717300768
Hargyatni, T., & Purnama, K. D. (2024). Impact analysis of artificial intelligence utilization in enhancing business decision-making in the financial sector. Jurnal Manajemen Indonesia, 4(1). https://jmi.stekom.ac.id/index.php/jmi/article/view/36
Karagozlu, D., Etswaka, J. N., & Babagil, M. T. (2024). Assessment of the effects of big data management on decision-making and business performance. In Digital Economy and New Value Creation (pp. 391–407). Springer. https://link.springer.com/chapter/10.1007/978-3-031-83207-9_29
Khair, M. A., Mahadasa, R., & Tuli, F. A. (2020). Beyond human judgment: Exploring the impact of artificial intelligence on HR decision-making efficiency and fairness. Semantic Scholar. https://pdfs.semanticscholar.org/1876/321c50cd91d5a49364c9654fbffdd52bcf29.pdf
Kumar, B. R., Reddy, S. M., Madhuri, A., & Shireesha, M. (2024). The role of artificial intelligence in decision-making processes. ResearchGate. https://www.researchgate.net/profile/Br-Kumar/publication/381767448_The_Role_of_Artificial_Intelligence_in_Decision-Making_Processes/links/667d9e16714e0b03152e58b3/The-Role-of-Artificial-Intelligence-in-Decision-Making-Processes.pdf
Li, L., Lin, J., Ouyang, Y., & Luo, X. R. (2022). Evaluating the impact of big data analytics usage on the decision-making quality of organizations. Technological Forecasting and Social Change, 180, 121716. https://www.sciencedirect.com/science/article/pii/S0040162521007861
Marimira, N., & Gumel, B. I. (2025). The role of artificial intelligence in strategic decision-making. Asian Journal of Economics, Business and Accounting. https://hal.science/hal-04983278/
Mazur, N., & Chukhray, N. (2023). The influence of modern technologies on the effectiveness of management and decision-making in organizations. Logos Science. https://archive.logos-science.com/index.php/conference-proceedings/article/view/678
Mongeon, P., & Paul-Hus, A. (2016). The journal coverage of Web of Science and Scopus: A comparative analysis. Scientometrics, 106, 213–228. https://doi.org/10.1007/s11192-015-1765-5
Neiroukh, S., Emeagwali, O. L., & Aljuhmani, H. Y. (2024). Artificial intelligence capability and organizational performance: Unraveling the mediating mechanisms of decision-making processes. Management Decision. https://doi.org/10.1108/MD-10-2023-1946
Nisar, Q. A., Nasir, N., Jamshed, S., & Naz, S. (2021). Big data management and environmental performance: Role of big data decision-making capabilities and decision-making quality. Journal of Enterprise Information Management, 34(3), 817–839. https://www.academia.edu/download/87880832/60120-Big-data-management-and-environmental-performance-role-of-big-data-decision-making-capabilities-and-decision-making-quality.pdf
Niu, Y., Ying, L., Yang, J., & Bao, M. (2021). Organizational business intelligence and decision making using big data analytics. Information Processing & Management, 58(4), 102620. https://doi.org/10.1016/j.ipm.2021.102620
Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., Chou, R., Glanville, J., Grimshaw, J. M., Hróbjartsson, A., Lalu, M. M., Li, T., Loder, E. W., Mayo-Wilson, E., McDonald, S., ... Moher, D. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ, 372, n71. https://doi.org/10.1136/bmj.n71
Rajagopal, N. K., Qureshi, N. I., & Durga, S. (2022). Future of business culture: An artificial intelligence–driven digital framework for organization decision-making process. Computational Intelligence and Neuroscience, 2022, 1–10. https://doi.org/10.1155/2022/7796507
Sadeghi, M. (2024). Analysis of the use of artificial intelligence in improving the decision-making process in the organization [Master’s thesis, BI Norwegian Business School]. BI Open. https://biopen.bi.no/bi-xmlui/bitstream/handle/11250/3167966/Master%20Thesis%20Final%20Version.pdf?sequence=1&isAllowed=y
Shamim, S., Zeng, J., Shariq, S. M., & Khan, Z. (2024). Role of big data management in enhancing big data decision-making capability and quality among Chinese firms: A dynamic capabilities view. Technological Forecasting and Social Change, 135, 12–21. https://kar.kent.ac.uk/70943/1/Role%20of%20big%20data%20management%20in%20enhancing%20big%20data%20decision.pdf
Shick, M., Johnson, N., & Fan, Y. (2024). Artificial intelligence and the end of bounded rationality: A new era in organizational decision making. Development and Learning in Organizations, 38(3), 8–11. https://www.emerald.com/insight/content/doi/10.1108/dlo-02-2023-0048/full/html
Shrestha, Y. R., & Ben-Menahem, S. M. (2019). Organizational decision-making structures in the age of artificial intelligence. California Management Review, 61(4), 66–83. https://doi.org/10.1177/0008125619862257
Teece, D. J. (2007). Explicating dynamic capabilities: The nature and microfoundations of (sustainable) enterprise performance. Strategic Management Journal, 28(13), 1319–1350. https://doi.org/10.1002/smj.640
Tummalapalli, H. K., Rao, A. N., Kamal, G., & Kumari, N. (2025). Exploring AI-driven management: Impact on organizational performance, decision making, efficiency, and employee engagement. ResearchGate. https://www.researchgate.net/profile/Hemanth-Tummalapalli/publication/384229531_Exploring_AI-Driven_Management_Impact_on_Organizational_Performance_Decision_Making_Efficiency_and_Employee_Engagement/links/672c423b77b63d1220e01943/Exploring-AI-Driven-Management-Impact-on-Organizational-Performance-Decision-Making-Efficiency-and-Employee-Engagement.pdf
van Eck, N. J., & Waltman, L. (2014). Visualizing bibliometric networks. In Y. Ding, R. Rousseau, & D. Wolfram (Eds.), Measuring scholarly impact (pp. 285–320). Springer. https://doi.org/10.1007/978-3-319-10377-8_13
Vincent, V. U. (2021). Integrating intuition and artificial intelligence in organizational decision-making. California Management Review, 63(2), 5–23. https://www.sciencedirect.com/science/article/pii/S0007681321000100
Wang, Y., & Byrd, T. A. (2021). Business analytics-enabled decision-making effectiveness through knowledge absorptive capacity in health care. Journal of Knowledge Management, 21(3), 517–539. https://www.emerald.com/insight/content/doi/10.1108/JKM-08-2015-0301/full/html
