Artificial Intelligence (AI) is also becoming not only a tool of technology but also a strategic organizational asset that has helped companies to adjust, innovate, and maintain a competitive advantage in dynamic markets. This study builds on the theory of Dynamic Capability, and the Resource-Based View (RBV): the concept of AI is developed as a higher-order dynamic capability, which upgrades the sensing, seizing, and reconfiguring capacity of firms. The study incorporates financial, operational and AI-specific metrics of innovation by using a cross-sectional dataset of 43 major technology and AI-intensive companies globally in 2024 (including the likes of NVIDIA, Microsoft, Alphabet and Amazon) to empirically test the relationship between AI capability and competitive performance. AI capability is modeled based on AI revenue percentage, AI patent counts, cloud revenue contribution, and GPU market share and sustained competitive advantage is proxied based on market capitalization, revenue growth and valuation metrics. The results indicate that companies that have more powerful AI-based abilities have a much higher growth rate and market valuation, implying that AI helps to bring agility at the firm-level and competitive positioning in the long-term perspective. The findings reveal that AI competence does not only increase the intensity of innovation, but also investor confidence, which supports the position of AI capability as a strategic resource and not an independent technology investment. This study makes a contribution to the literature related to strategy management because it provides empirical data that AI is a dynamic ability, which affects competitive advantage in the digital economy. It provides managerial insights to executives who aim to use AI investments to create sustainable values as well. The study contributes to the knowledge of AI metrics in the context of the firm performance indicators, thus, moving AI metrics in terms of relevant outcomes of the digital transformation to the realms of competitive practices.
Keywords
Artificial Intelligence, Dynamic Capability, Constant Competitive Advantage. Resource-Based View (RBV), AI Capability Index and Strategic Management
Conclusion
This study has discussed Artificial Intelligence (AI) as a dynamic element of capabilities and the prospects of its relevance in the context of the long-term competitive advantage of global technology giants. The research was based on the Dynamic Capability Theory and the Resource based View, and the conceptualization of AI was that of a technological investment, but an intrinsic organizational ability that affects financial performance, market position, and growth results. The combination of AI-specific innovation indicators with financial and operational ones enabled the study to offer empirical data on the strategic role AI plays in the modern digital markets. The results show that AI capability, which is gauged by AI revenue intensity, patent activity, cloud revenue and GPU market share, has a positive relationship with firm valuation and financial scale. Companies that show greater integration of AI and intensity of innovation are more likely to have increased market capitalization and performance in revenues. These findings confirm the theoretical hypothesis that difficult-to-replicate and essential, systematic, and hidden technological capabilities are part of competitive differentiation. Nonetheless, the distributional and predictive studies indicate that the capacity to use AI does not alone with certainty lead to short-term growth. Although AI will be useful in structural competitive power, variability of growth across firms brings to light the relevance of complementary resources, strategic implementation and market circumstances. The results of the machine learning classification further indicate that even though AI indicators have explanatory relevance, they do not have explanatory predictive ability when alone in classifying annual growth. This further supports the thesis that AI would best serve as a strategic facilitator in the long term and not a short-term predictor of growth. An enduring competitive advantage is developed in the case of the use of AI ability that is combined with organizational learning, innovation governance, and scalable business models. the research contributes to the body of strategic management literature by demonstrating through empirical study that AI is a dynamic capability that has an impact on competitive positioning. It helps in the dichotomy between the theoretical conceptualization and the quantifiable firm level performance results. Digital transformation is gaining momentum and organizations need to go past AI adoption to integrate ability and be strategic to achieve sustainable value. The results offer scholarly and managerial implications of capitalizing on AI investments to gain a sustainable competitive advantage in the fast-paced changing technological landscapes.
References
1.Lechner, Paul, and Thomas Lindner. “THE STRATEGIC INFLUENCE OF ARTIFICIAL INTELLIGENCE ON THE INTERNATIONALIZATION OF AUSTRIAN INDUSTRIES BASED ON THE DYNAMIC CAPABILITIES THEORY.”
2.Costa, F., Digital Business Model Innovation: Integrating Artificial Intelligence for Competitive Advantage and Organizational Transformation.
3.Dunaway Virginia, Mary, Yulia W. Sullivan, and Samuel Fosso Wamba. “Building dynamic capabilities with the internet of things.” (2019).
4.Fainshmidt, Stav, Lucas Wenger, Amir Pezeshkan, and Mark R. Mallon. “When do dynamic capabilities lead to competitive advantage? The importance of strategic fit.” Journal of Management Studies 56, no. 4 (2019): 758-787.
5.Mikalef, Patrick, Maria Boura, George Lekakos, and John Krogstie. “Big data analytics capabilities and innovation: the mediating role of dynamic capabilities and moderating effect of the environment.” British journal of management 30, no. 2 (2019): 272-298.
6.Gupta, S., Qian, X., Bhushan, B., & Luo, Z. (2019). Role of cloud ERP and big data on firm performance: a dynamic capability view theory perspective. Management decision, 57(8), 1857-1882.
7.van de Wetering, Rogier, Patrick Mikalef, and Adamantia Pateli. “Strategic alignment between IT flexibility and dynamic capabilities: An empirical investigation.” International Journal of IT/Business Alignment and Governance (IJITBAG) 9, no. 1 (2018): 1-20.
8.Shamim, Saqib, Jing Zeng, Syed Muhammad Shariq, and Zaheer Khan. “Role of big data management in enhancing big data decision-making capability and quality among Chinese firms: A dynamic capabilities view.” Information & Management 56, no. 6 (2019): 103135.9.Garbellano, Salvatore, and Maria do Rosário Da Veiga. “Dynamic capabilities in Italian leading SMEs adopting industry 4.0.” Measuring Business Excellence 23, no. 4 (2019): 472-483.
10.Rialti, Riccardo, Giacomo Marzi, Cristiano Ciappei, and Donatella Busso. “Big data and dynamic capabilities: a bibliometric analysis and systematic literature review.” Management Decision 57, no. 8 (2019): 2052-2068.
11.Ma H, Sun Q, Gao Y, Gao Y. Resource integration, reconfiguration, and sustainable competitive advantages: the differences between traditional and emerging industries. Sustainability. 2019 Jan 21;11(2):551.
12.Mention, Anne-Laure, Pierre-Jean Barlatier, and Emmanuel Josserand. “Using social media to leverage and develop dynamic capabilities for innovation.” Technological Forecasting and Social Change 144 (2019): 242-250.
13.Kurtz DJ, Varvakis G. Dynamic capabilities and organizational resilience in turbulent environments. InCompetitive strategies for small and medium enterprises: Increasing crisis resilience, agility and innovation in turbulent times 2016 Feb 20 (pp. 19-37). Cham: Springer International Publishing.
14.Mousavi, Seyedesmaeil, Bart Bossink, and Mario van Vliet. “Microfoundations of companies’ dynamic capabilities for environmentally sustainable innovation: Case study insights from high‐tech innovation in science‐based companies.” Business Strategy and the Environment 28.2 (2019): 366-387.
15.Tuohimaa, Hannele. Microfoundations of dynamic capabilities in retail in the age of artificial intelligence and robotics. MS thesis. H. Tuohimaa, 2019.
16.Nayak, Bishwajit, Som Sekhar Bhattacharyya, and Bala Krishnamoorthy. “Integrating wearable technology products and big data analytics in business strategy: A study of health insurance firms.” Journal of Systems and Information Technology 21.2 (2019): 255-275.
17.Nayak, Bishwajit, Som Sekhar Bhattacharyya, and Bala Krishnamoorthy. “Integrating wearable technology products and big data analytics in business strategy: A study of health insurance firms.” Journal of Systems and Information Technology 21.2 (2019): 255-275.
18.Teece, David J. “A dynamic capabilities-based entrepreneurial theory of the multinational enterprise.” The eclectic paradigm: A framework for synthesizing and comparing theories of international business from different disciplines or perspectives. London: Palgrave Macmillan UK, 2016. 224-273.
19.Dubey, Rameshwar, Angappa Gunasekaran, Stephen J. Childe, Thanos Papadopoulos, Zongwei Luo, Samuel Fosso Wamba, and David Roubaud. “Can big data and predictive analytics improve social and environmental sustainability?.” Technological forecasting and social change 144 (2019): 534-545.
20.Rebs, Tobias, Daniel Thiel, Marcus Brandenburg, and Stefan Seuring. “Impacts of stakeholder influences and dynamic capabilities on the sustainability performance of supply chains: a system dynamics model: T. Rebs et al.” Journal of Business Economics 89, no. 7 (2019): 893-926.
21.Fainshmidt S, Wenger L, Pezeshkan A, Mallon MR. When do dynamic capabilities lead to competitive advantage? The importance of strategic fit. Journal of Management Studies. 2019 Jun;56(4):758-87.
22.Mikalef, P., Boura, M., Lekakos, G., & Krogstie, J. (2019). Big data analytics capabilities and innovation: the mediating role of dynamic capabilities and moderating effect of the environment. British journal of management, 30(2), 272-298.
23.Schwarz JO, Rohrbeck R, Wach B. Corporate foresight as a microfoundation of dynamic capabilities. Futures & foresight science. 2020 Jun;2(2):e28.
24.Gupta, Shivam, Xiaoyan Qian, Bharat Bhushan, and Zongwei Luo. “Role of cloud ERP and big data on firm performance: a dynamic capability view theory perspective.” Management decision 57, no. 8 (2019): 1857-1882.
25.Qiu L, Jie X, Wang Y, Zhao M. Green product innovation, green dynamic capability, and competitive advantage: Evidence from Chinese manufacturing enterprises. Corporate Social Responsibility and Environmental Management. 2020 Jan;27(1):146-65.
26.Čirjevskis A. The role of dynamic capabilities as drivers of business model innovation in mergers and acquisitions of technology-advanced firms. Journal of Open Innovation: Technology, Market, and Complexity. 2019 Mar 4;5(1):12.
27.Shamim, Saqib, Jing Zeng, Syed Muhammad Shariq, and Zaheer Khan. “Role of big data management in enhancing big data decision-making capability and quality among Chinese firms: A dynamic capabilities view.” Information & Management 56, no. 6 (2019): 103135.
28.Shamim, Saqib, Jing Zeng, Syed Muhammad Shariq, and Zaheer Khan. “Role of big data management in enhancing big data decision-making capability and quality among Chinese firms: A dynamic capabilities view.” Information & Management 56, no. 6 (2019): 103135.
29.Bag, Surajit, Shivam Gupta, and Zongwei Luo. “Examining the role of logistics 4.0 enabled dynamic capabilities on firm performance.” The international journal of logistics management 31.3 (2020): 607-628.
30.Garbellano, Salvatore, and Maria do Rosário Da Veiga. “Dynamic capabilities in Italian leading SMEs adopting industry 4.0.” Measuring Business Excellence 23.4 (2019): 472-483.
31.Rialti, Riccardo, Giacomo Marzi, Cristiano Ciappei, and Donatella Busso. “Big data and dynamic capabilities: a bibliometric analysis and systematic literature review.” Management Decision 57, no. 8 (2019): 2052-2068.
32.Gupta, S., Modgil, S., Gunasekaran, A. and Bag, S., 2020, July. Dynamic capabilities and institutional theories for Industry 4.0 and digital supply chain. In Supply Chain Forum: An International Journal (Vol. 21, No. 3, pp. 139-157). Taylor & Francis.
33.Mention, Anne-Laure, Pierre-Jean Barlatier, and Emmanuel Josserand. “Using social media to leverage and develop dynamic capabilities for innovation.” Technological Forecasting and Social Change 144 (2019): 242-250.
34.Khan, Owais, Tiberio Daddi, and Fabio Iraldo. “Microfoundations of dynamic capabilities: Insights from circular economy business cases.” Business Strategy and the Environment 29, no. 3 (2020): 1479-1493.
35.Mousavi S, Bossink B, van Vliet M. Microfoundations of companies’ dynamic capabilities for environmentally sustainable innovation: Case study insights from high‐tech innovation in science‐based companies. Business Strategy and the Environment. 2019 Feb;28(2):366-87.
36.Witschel D, Döhla A, Kaiser M, Voigt KI, Pfletschinger T. Riding on the wave of digitization: Insights how and under what settings dynamic capabilities facilitate digital-driven business model change. Journal of Business Economics. 2019 Dec;89(8):1023-95
37.Witschel D, Döhla A, Kaiser M, Voigt KI, Pfletschinger T. Riding on the wave of digitization: Insights how and under what settings dynamic capabilities facilitate digital-driven business model change. Journal of Business Economics. 2019 Dec;89(8):1023-95.
38.Irfan, Muhammad, Mingzheng Wang, and Naeem Akhtar. “Impact of IT capabilities on supply chain capabilities and organizational agility: a dynamic capability view: Irfan M. et al.” Operations Management Research 12.3 (2019): 113-128.
39.Sousa-Zomer, T. T., Neely, A., & Martinez, V. (2020). Digital transforming capability and performance: a microfoundational perspective. International Journal of Operations & Production Management, 40(7-8), 1095-1128.
40.Nayak A, Chia R, Canales JI. Noncognitive microfoundations: Understanding dynamic capabilities as idiosyncractically refined sensitivities and predispositions. Academy of Management Review. 2020 Apr;45(2):280-303.
How to Cite This Paper
Md Mehedi Hassan Melon, Maria Kabtia, Md Mahidur Rahman, MD Monirul Islam, Md Azharul Islam, Md Sumon Rana, Nayem Miah, MD Mizanur Rahman, Md Fazlay Rabby (2025). Artificial Intelligence as a Dynamic Capability: Implications for Sustained Competitive Advantage. International Journal of Computer Techniques, 12(1). ISSN: 2394-2231.
