المجلة الدولية لنشر البحوث والدراسات

International Journal of Research and Studies Publishing

المجلة الدولية لنشر البحوث والدراسات

Organizational AI Capability: From Algorithmic Capital to Sustainable Competitive Advantage

By: Dr. Mohammad Saad Abuhaimed

PhD in Business Management, Researcher & Senior Management Consultant, MCM Consultancy, Saudi Arabia


Abstract:

The pace of artificial intelligence (AI) across industries has created a paradox: numerous organizations purchase AI technologies and even build up an arsenal of algorithms, yet many fail to transform this purchase into sustainable benefit. The construct that is most frequently called upon to give an explanation of this gap- AI capability- is still conceptually disjointed. Earlier literature has focused on adoption, preparation, maturity, and resource collection, and a parallel line has started to consider algorithmic assets as a specific strategic resource (algorithmic capital). The transformation, i.e., how organizations transform algorithmic capital and other resources into a higher-order organizational AI capability, and why that capability should be able to create value, is what is unspecified. The present paper builds up an integrative transformation theory based on the Resource-Based View, the Knowledge-Based View, the Dynamic Capabilities perspective, and Organizational Learning theory. We characterize the organizational AI capability as a higher-order, multidimensional construct; present a three-level architecture that bridges AI resources (including algorithmic capital), mid-level capability constructs, and an emergent organizational capability; describe a formation mechanism; develop seven propositions; and state the boundary conditions. The contribution is a coherent account of how firms move from possessing algorithmic capital to possessing an AI-based organizational capability, and from that capability to competitive advantage.


Keywords:

organizational AI capability; algorithmic capital; resource-based view; knowledge-based view; business engineering; competitive advantage.

PhD in Business Management, Researcher & Senior Management Consultant, MCM Consultancy, Saudi Arabia

- Abuhaimed, M. S. (2026a). From business management to business engineering: A conceptual analysis of the transformation of management practice in the digital era. Arab Journal of Administration. https://doi.org/10.21608/AJA.2026.497161.2118
- Abuhaimed, M. S. (2026b). Algorithmic capital governance in the age of artificial intelligence: A conceptual framework grounded in the resource-based view (RBV) and intellectual capital theory. International Journal of Financial, Administrative and Economic Sciences, 5(6), 226–238. https://doi.org/10.59992/IJFAES.2026.v5n6p13
- Abuhaimed, M. S., Aljounaidi, A., & Ateik, A. (2024). Reframing talent management in the digital era: A systematic review on its role in facilitating knowledge sharing and AI adoption in emerging tech startups. International Journal of Finance and Management, 6(1). https://ojs.mediu.edu.my/index.php/IJFM/article/view/5586
- Abuhaimed, M. S., Aljounaidi, A., & Ateik, A. (2025). Talent management strategies and AI adoption in Saudi tech startups: Empirical evidence on the mediating role of knowledge sharing. International Journal of Research and Innovation in Social Science, 9(8), 3944–3949. https://doi.org/10.47772/IJRISS.2025.908000318
- Abou-Foul, M., Ruiz-Alba, J. L., & López-Tenorio, P. J. (2023). The impact of artificial intelligence capabilities on servitization: The moderating role of absorptive capacity—A dynamic capabilities perspective. Journal of Business Research, 157, 113609. https://doi.org/10.1016/j.jbusres.2022.113609
- Agarwal, R., Gao, G., DesRoches, C., & Jha, A. K. (2010). Research commentary—The digital transformation of healthcare: Current status and the road ahead. Information Systems Research, 21(4), 796–809. https://doi.org/10.1287/isre.1100.0327
- Alsheibani, S., Cheung, Y., & Messom, C. (2018). Artificial intelligence adoption: AI-readiness at firm-level. Proceedings of the Pacific Asia Conference on Information Systems (PACIS).
- Argyris, C., & Schön, D. A. (1978). Organizational learning: A theory of action perspective. Addison-Wesley.
- Barney, J. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17(1), 99–120. https://doi.org/10.1177/014920639101700108
- Bostrom, R. P., & Heinen, J. S. (1977). MIS problems and failures: A socio-technical perspective. Part I: The causes. MIS Quarterly, 1(3), 17–32. https://doi.org/10.2307/248710
- Brynjolfsson, E., & McAfee, A. (2014). The second machine age: Work, progress, and prosperity in a time of brilliant technologies. W. W. Norton.
- Cockburn, I. M., Henderson, R., & Stern, S. (2018). The impact of artificial intelligence on innovation (NBER Working Paper No. 24449). National Bureau of Economic Research. https://doi.org/10.3386/w24449
- Felin, T., Foss, N. J., Heimeriks, K. H., & Madsen, T. L. (2012). Microfoundations of routines and capabilities: Individuals, processes, and structure. Journal of Management Studies, 49(8), 1351–1374. https://doi.org/10.1111/j.1467-6486.2012.01052.x
- Galbraith, J. R. (1977). Organization design. Addison-Wesley.
- Grant, R. M. (1996). Toward a knowledge-based theory of the firm. Strategic Management Journal, 17(S2), 109–122. https://doi.org/10.1002/smj.4250171110
- Iansiti, M., & Lakhani, K. R. (2020). Competing in the age of AI: Strategy and leadership when algorithms and networks run the world. Harvard Business Review Press.
- Khan, S., Khan, K. U., & Mehmood, S. (2025). AI maturity in manufacturing: The role of generative AI in driving organizational performance through exploratory and exploitative innovation. Benchmarking: An International Journal. Advance online publication. https://doi.org/10.1108/BIJ-01-2025-0099
- March, J. G. (1991). Exploration and exploitation in organizational learning. Organization Science, 2(1), 71–87. https://doi.org/10.1287/orsc.2.1.71
- 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. Information & Management, 56(8), 103169. https://doi.org/10.1016/j.im.2019.03.003
- Mikalef, P., & Gupta, M. (2021). Artificial intelligence capability: Conceptualization, measurement calibration, and empirical study on its impact on organizational creativity and firm performance. Information & Management, 58(3), 103434. https://doi.org/10.1016/j.im.2021.103434
- 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, 63(10), 3501–3532. https://doi.org/10.1108/MD-10-2023-1946
- Nonaka, I. (1994). A dynamic theory of organizational knowledge creation. Organization Science, 5(1), 14–37. https://doi.org/10.1287/orsc.5.1.14
- Papagiannidis, E., Mikalef, P., & Conboy, K. (2025). Responsible artificial intelligence governance: A review and research framework. The Journal of Strategic Information Systems, 34(2), 101885. https://doi.org/10.1016/j.jsis.2024.101885
- Peteraf, M. A. (1993). The cornerstones of competitive advantage: A resource-based view. Strategic Management Journal, 14(3), 179–191. https://doi.org/10.1002/smj.4250140303
- Prasad Agrawal, K. (2024). Towards adoption of generative AI in organizational settings. Journal of Computer Information Systems, 64(5), 636–651. https://doi.org/10.1080/08874417.2023.2240744
- Rajaram, K., & Tinguely, P. N. (2024). Generative artificial intelligence in small and medium enterprises: Navigating its promises and challenges. Business Horizons, 67(5), 629–648. https://doi.org/10.1016/j.bushor.2024.05.005
- Ransbotham, S., Kiron, D., Gerbert, P., & Reeves, M. (2017). Reshaping business with artificial intelligence. MIT Sloan Management Review.
- Sonntag, M., Mehmann, S., Mehmann, J., & Teuteberg, F. (2024). Development and evaluation of a maturity model for AI deployment capability of manufacturing companies. Information Systems Management, 42(1), 37–67. https://doi.org/10.1080/10580530.2024.2319041
- Storey, V. C., Yue, W. T., Zhao, J. L., & Lukyanenko, R. (2025). Generative artificial intelligence: Evolving technology, growing societal impact, and opportunities for information systems research. Information Systems Frontiers, 27, 2081–2102. https://doi.org/10.1007/s10796-025-10581-7
- 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
- Teece, D. J., Pisano, G., & Shuen, A. (1997). Dynamic capabilities and strategic management. Strategic Management Journal, 18(7), 509–533. https://doi.org/10.1002/(SICI)1097-0266(199708)18:7<509::AID-SMJ882>3.0.CO;2-Z
- Whetten, D. A. (1989). What constitutes a theoretical contribution? Academy of Management Review, 14(4), 490–495. https://doi.org/10.5465/amr.1989.4308371
- Winter, S. G. (2003). Understanding dynamic capabilities. Strategic Management Journal, 24(10), 991–995. https://doi.org/10.1002/smj.318







المجلة الدولية لنشر البحوث والدراسات

المجلة الدولية لنشر البحوث والدراسات مجلة علمية محكمة دولية متخصصة في نشر الأبحاث العلمية الأصيلة، تصدر المجلة الدولية دورياً كل شهر. تصدر المجلة في المملكة الأردنية الهاشمية

للإقتراحات


نحن نعمل باستمرار على تحسين مجلتنا العلمية وعملية النشر لدينا بهدف تزويدك بأفضل تجربة نشر علمية. فإننا نقدر رأيك ونرحب بأي اقتراحات عبر الإيميل التالي: info@ijrsp.com

جميع الحقوق محفوظة © المجلة الدولية لنشر البحوث والدراسات 2019-2026م