Issue: № 2, 2025
Doi: https://doi.org/10.37634/efp.2025.2.6
This purpose of the paper is to develop a conceptual framework that seamlessly combines established strategic management principles with the transformative capabilities of AI. By examining the integration of dynamic capabilities, the strategic role of data and algorithms, and the ethical and leadership challenges associated with AI adoption, the study seeks to identify practical approaches for leveraging AI as a core strategic asset. The objective is to facilitate the transition from traditional, plan-based strategies to adaptive, learning-oriented models that support sustainable competitive advantages in a volatile market environment. The research findings demonstrate that integrating AI into strategic management not only enhances operational efficiency but also creates new avenues for competitive differentiation. Through detailed case analyses—ranging from logistics optimization and real-time inventory management to personalized customer service and adaptive pricing models—the study reveals that AI transforms vast amounts of structured and unstructured data into actionable insights. These insights enable companies to predict market trends with high accuracy, automate decision-making processes, and rapidly adjust to evolving consumer demands. Moreover, the results emphasize that aligning AI technologies with organizational culture and leadership is crucial for mitigating risks related to data quality, ethical concerns, and potential strategic imitation by competitors. In conclusion, the integration of AI into strategic management represents a powerful mechanism for companies to not only optimize internal processes but also to build and sustain long-term competitive advantages. The proposed framework bridges the gap between classical strategic theories and contemporary digital capabilities, offering a practical roadmap for business leaders navigating the complexities of digital transformation. Future research should further refine the methodologies for assessing AI-driven strategic initiatives and explore the broader impact of AI on evolving business models. Ultimately, AI stands as a catalyst for continuous innovation and strategic growth, enabling enterprises to thrive in an increasingly dynamic and uncertain market landscape.
Keywords : artificial intelligence, strategic management, dynamic capabilities, competitive advantage, digital transformation, innovation, competitiveness
References:
2. Barney J.B. Firm resources and sustained competitive advantage. Journal of Management, 1991. № 17(1). pp. 99–120. URL: https://doi.org/10.1177/014920639101700108
3. Brynjolfsson E., McAfee A. (). Machine, platform, crowd: Harnessing our digital future. W.W. Norton & Company, 2017.
4. Chui M., Manyika J., Miremadi M. What AI can and can’t do (yet) for your business. McKinsey Quarterly, 2018.
5. Collis D.J., Montgomery C.A. Corporate strategy: Resources and the scope of the firm. Irwin/McGraw-Hill, 1997.
6. Davenport T.H., Ronanki R. Artificial intelligence for the real world. Harvard Business Review. 2018. № 96(1). pp. 108–116.
7. Eisenhardt K.M., Martin J.A. Dynamic capabilities: What are they? Strategic Management Journal. 2000. № 21(10‐11). pp. 1105–1121. URL: https://doi.org/10.1002/1097-0266(200010/11)21:10/11<1105::AID-SMJ133>3.0.CO;2-E
8. Grant R.M. Contemporary strategy analysis. John Wiley & Sons, 2016.
9. Haenlein M., Kaplan A. A brief history of artificial intelligence: On the past, present, and future of artificial intelligence. California Management Review. 2019. № 61(4). pp. 5–14 URL: https://doi.org/10.1177/0008125619864925
10. Hamel G., Prahalad C.K. Competing for the future. Harvard Business School Press, 1994.
11. Kaplan R.S., Norton D.P. The balanced scorecard: Translating strategy into action. Harvard Business School Press, 1996.
12. Kotter J.P. Leading change. Harvard Business Review Press, 1996.
13. Mintzberg H. The rise and fall of strategic planning. Free Press, 1994.
14. Porter M.E. Competitive strategy: Techniques for analyzing industries and competitors. Free Press, 1980.
15. Rumelt R.P. Good strategy bad strategy: The difference and why it matters. Crown Business, 2011.
16. Russell S., Norvig P. Artificial intelligence: A modern approach. Pearson, 2020.
17. Shrestha Y.R., Ben-Menahem S.M., von Krogh G. Organizational decision-making structures in the age of artificial intelligence. California Management Review. 2019. № 61(4). pp. 66–83 URL: https://doi.org/10.1177/0008125619862257
18. Tambe P., Cappelli P., Yakubovich V. Artificial intelligence in human resources management: Challenges and a path forward. California Management Review. 2019. № 61(4). pp. 15–42. URL: https://doi.org/10.1177/0008125619867910
19. Teece D.J. Managing the intangible economy: Business models and the digital enterprise. California Management Review. 2018. № 60(2). pp. 12–24. URL: https://doi.org/10.1177/0008125617738526
20. Teece D.J., Pisano G., Shuen A. Dynamic capabilities and strategic management. Strategic Management Journal. 1997. № 18(7). pp. 509–533. URL: https://doi.org/10.1002/(SICI)1097-0266(199708)18:7<509::AID-SMJ882>3.0.CO;2-Z
21. Thompson A.A., Peteraf M.A., Gamble J.E., Strickland A.J. Crafting and executing strategy: The quest for competitive advantage. McGraw-Hill Education, 2016.
22. Wernerfelt B. A resource-based view of the firm. Strategic Management Journal. 1984. № 5(2). pp. 171–180. URL: https://doi.org/10.1002/smj.4250050207