From Data Assets to Value Creation: Competitive Advantage in the AI Age
Article Sidebar
Main Article Content
Abstract
The rapid advancement of Artificial Intelligence (AI) has fundamentally transformed how organizations create and sustain competitive advantage. In contemporary business environments, data is no longer treated merely as a supporting asset but has emerged as a primary source of value creation. This article examines how data-driven approaches, enabled by AI technologies, generate competitive advantage through enhanced decision-making, personalization, and operational efficiency. Using a conceptual research method, this study synthesizes findings from international peer-reviewed journals to analyze the mechanisms through which data becomes economic value. The Results and Discussion section elaborates on three core dimensions: the transformation of data into value generators, the economic characteristics of data in AI-driven markets, and the strategic logic of value creation through data–algorithm–context alignment. The findings indicate that data-driven competitive advantage is contingent not only on data volume but also on data quality, governance, and organizational capability. This article contributes to the growing body of literature on AI-enabled strategy by offering an integrated framework for understanding data as a strategic source of competitive advantage.
Downloads
Article Details
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Accepted 2025-12-29
Published 2025-12-29
Plaudit
References
J. B. Barney, “Firm resources and sustained competitive advantage,” in Economics Meets Sociology in Strategic Management. Bingley, U.K.: Emerald Group Publishing Limited, 2000, pp. 203–227.
S. El Nemar, H. El-Chaarani, I. Dandachi, and S. Castellano, “Resource-based view and sustainable advantage: A framework for SMEs,” J. Strategic Marketing, vol. 33, no. 6, pp. 798–821, 2025.
J. Gao and Z. Sarwar, “How do firms create business value and dynamic capabilities by leveraging big data analytics management capability?” Inf. Technol. Manag., vol. 25, no. 3, pp. 283–304, 2024.
K. Ansari and M. Ghasemaghaei, “Big data analytics capability and firm performance: A meta-analysis,” J. Comput. Inf. Syst., vol. 63, no. 6, pp. 1477–1494, 2023.
A. Bany Mohammad, M. Al-Okaily, M. Al-Majali, and R. E. Masa’deh, “Business intelligence and analytics (BIA) usage in the banking industry sector: An application of the TOE framework,” J. Open Innov.: Technol., Market, Complexity, vol. 8, no. 4, Art. no. 189, 2022.
S. H. Bhatti, A. Ahmed, A. Ferraris, W. M. Hirwani Wan Hussain, and S. F. Wamba, “Big data analytics capabilities and MSME innovation and performance: A double mediation model of digital platform and network capabilities,” Ann. Oper. Res., vol. 350, no. 2, pp. 729–752, 2025.
N. Hajiheydari, M. Kargar Shouraki, H. Vares, and A. Mohammadian, “Digital sustainable business model innovation: Applying dynamic capabilities approach (DSBMI-DC),” Foresight, vol. 25, no. 3, pp. 420–447, 2023.
C. Sousa, M. Mmadubuko, R. Sadraei, and V. J. Sadeghi, “Disruptive technology and trends in SME digital internationalisation: A systematic review and new research agenda,” in Navigating Disruptions and Transformations in International Business. Cham, Switzerland: Springer, 2025, pp. 289–312.
G. Cao, N. Tian, and C. Blankson, “Big data, marketing analytics, and firm marketing capabilities,” J. Comput. Inf. Syst., vol. 62, no. 3, pp. 442–451, 2022.
S. Shimpi, “The underlying foundation for the e-commerce customer shopping experience edge with big data analytics,” in Augmenting Customer Retention Through Big Data Analytics. Boca Raton, FL, USA: Apple Academic Press, 2024, pp. 71–85.
K. Martin, Ethics of Data and Analytics: Concepts and Cases. Boca Raton, FL, USA: Auerbach Publications, 2022.
J. Xavier and W. N. Picoto, “Regulation of data-driven marketing and management theory: Bibliometric analysis, systematic literature review and research agenda,” Int. J. Law Manag., vol. 65, no. 5, pp. 461–482, 2023.
R. Dahiya, S. Le, J. K. Ring, and K. Watson, “Big data analytics and competitive advantage: The strategic role of firm-specific knowledge,” J. Strategy Manag., vol. 15, no. 2, pp. 175–193, 2022.
D. Oliveira-Dias, J. M. Kneipp, R. S. Bichueti, and C. M. Gomes, “Fostering business model innovation for sustainability: A dynamic capabilities perspective,” Manag. Decis., vol. 60, no. 13, pp. 105–129, 2022.
S. Vudugula, S. K. Chebrolu, M. Bhuiyan, and F. Z. Rozony, “Integrating artificial intelligence in strategic business decision-making: A systematic review of predictive models,” Int. J. Sci. Interdisciplinary Res., vol. 4, no. 1, pp. 1–26, 2023.
G. Ben-Ishai, J. Dean, J. Manyika, R. Porat, H. Varian, and K. Walker, “AI and the opportunity for shared prosperity: Lessons from the history of technology and the economy,” arXiv preprint, arXiv:2401.09718, 2024.
Y. Lu and Y. Zhou, “A review on the economics of artificial intelligence,” J. Econ. Surveys, vol. 35, no. 4, pp. 1045–1072, 2021.
E. Brynjolfsson, D. Rock, and C. Syverson, “The productivity J-curve: How intangibles complement general purpose technologies,” Amer. Econ. J.: Macroecon., vol. 13, no. 1, pp. 333–372, 2021.
A. Benabou, F. Touhami, and L. Demraoui, “Artificial intelligence and the future of human resource management,” in Proc. 2024 Int. Conf. Intelligent Systems and Computer Vision (ISCV). IEEE, 2024, pp. 1–8.
L. D. Yiu, A. C. Yeung, and T. E. Cheng, “The impact of business intelligence systems on profitability and risks of firms,” Int. J. Prod. Res., vol. 59, no. 13, pp. 3951–3974, 2021.
E. Attah and M. I. Anaba, “Harnessing artificial intelligence for business and entrepreneurship transformation: Enhancing processes, decision-making, and customer experiences,” 2025.
S. Sultana, S. Akter, and E. Kyriazis, “Theorising data-driven innovation capabilities to survive and thrive in the digital economy,” J. Strategic Marketing, vol. 32, no. 7, pp. 864–890, 2024.
I. Firdausa Nuzula and M. Miftahul Amri, “Will ChatGPT bring a New Paradigm to HR World? A Critical Opinion Article”, J. Man. Stu. Dev., vol. 2, no. 02, pp. 142–161, Apr. 2023.