The Role of Artificial Intelligence in Shaping Global Market Strategies and Economic Decision-Making among Multinational Corporations

Artificial intelligence (AI) is a key technical innovation impacting business strategy, long-term viability of businesses, and economic decisions in rapidly changing digital marketplaces. Multinational companies that use AI technology have a great impact on their strategy plan, on the way they interact customers, on their operational efficiency and on their capacity to compete in the global market. This study is concerned with the impact of Artificial Intelligence (AI) on economic decision-making and strategy planning of transnational enterprises in world markets. The research utilizes secondary data analysis derived from international economic papers, AI industry publications, and global business databases released throughout 2020-2025. Qualitative descriptive methodology is used. The findings point to AI’s role in making it easier to predict the market, generate targeted marketing campaigns, run organizations more efficiently, and make data-driven decisions. The study concludes that AI increases the competitiveness of international companies, provides them with additional strategic options and allows them to survive for a long period in rapidly changing global digital markets.

Artificial Intelligence, Global Market Strategies, Economic Decision-Making

1. Barney, J. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17(1), 99–120. https://doi.org/10.1177/014920639101700108 [Google Scholar] [Crossref]

2. Brynjolfsson, E., & McAfee, A. (2017). Machine, platform, crowd: Harnessing our digital future. W. W. Norton & Company. [Google Scholar] [Crossref]

3. Chui, M., Manyika, J., & Miremadi, M. (2018). What AI can and can’t do (yet) for your business. McKinsey Quarterly, 1(1), 1–9. [Google Scholar] [Crossref]

4. Davenport, T. H., & Ronanki, R. (2018). Artificial intelligence for the real world. Harvard Business Review, 96(1), 108–116. [Google Scholar] [Crossref]

5. Dwivedi, Y. K., Hughes, L., Baabdullah, A. M., et al. (2023). So what if ChatGPT wrote it? Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy. International Journal of Information Management, 71, 102642. https://doi.org/10.1016/j.ijinfomgt.2023.102642 [Google Scholar] [Crossref]

6. Gartner. (2025). Top strategic technology trends 2025: Artificial intelligence and digital transformation. Gartner Research. https://www.gartner.com [Google Scholar] [Crossref]

7. George, G., Lakhani, K. R., & Puranam, P. (2020). What has changed? The impact of Artificial Intelligence on the organization of work. Academy of Management Discoveries, 6(4), 544–568. https://doi.org/10.5465/amd.2019.0186 [Google Scholar] [Crossref]

8. Huang, M. H., & Rust, R. T. (2021). A strategic framework for artificial intelligence in marketing. Journal of the Academy of Marketing Science, 49(1), 30–50. https://doi.org/10.1007/s11747-020-00749-9 [Google Scholar] [Crossref]

9. International Monetary Fund. (2025). Artificial intelligence and the future of work in global economies. IMF Publications. https://www.imf.org [Google Scholar] [Crossref]

10. Johnston, M. P. (2017). Secondary data analysis: A method of which the time has come. Qualitative and Quantitative Methods in Libraries, 3(3), 619–626. [Google Scholar] [Crossref]

11. Kaplan, A., & Haenlein, M. (2020). Rulers of the world, unite! The challenges and opportunities of Artificial Intelligence. Business Horizons, 63(1), 37–50. https://doi.org/10.1016/j.bushor.2019.09.003 [Google Scholar] [Crossref]

12. Kshetri, N. (2021). Artificial Intelligence in global supply chains and international business operations. IT Professional, 23(4), 11–15. https://doi.org/10.1109/MITP.2021.3079150 [Google Scholar] [Crossref]

13. McKinsey & Company. (2025). The state of AI in 2025: Generative AI’s organizational impact. https://www.mckinsey.com [Google Scholar] [Crossref]

14. Mikalef, P., Boura, M., Lekakos, G., & Krogstie, J. (2019). Big data analytics capabilities and innovation: The mediating role of dynamic capabilities. Information and Management, 56(8), 103169. https://doi.org/10.1016/j.im.2019.04.003 [Google Scholar] [Crossref]

15. OECD. (2025). The adoption of artificial intelligence in firms. OECD Publishing. https://www.oecd.org [Google Scholar] [Crossref]

16. PwC. (2025). Sizing the prize: The economic impact of AI on global business. PricewaterhouseCoopers. https://www.pwc.com [Google Scholar] [Crossref]

17. Shrestha, Y. R., Ben-Menahem, S. M., & Von Krogh, G. (2019). Organizational decision-making structures in the age of Artificial Intelligence. California Management Review, 61(4), 66–83. https://doi.org/10.1177/0008125619862257 [Google Scholar] [Crossref]

18. Stanford Institute for Human-Centered Artificial Intelligence. (2025). Artificial intelligence index report 2025. Stanford University. https://hai.stanford.edu/ai-index [Google Scholar] [Crossref]

19. Teece, D. J., Peteraf, M., & Leih, S. (2016). Dynamic capabilities and organizational agility: Risk, uncertainty, and strategy in the innovation economy. California Management Review, 58(4), 13–35. https://doi.org/10.1525/cmr.2016.58.4.13 [Google Scholar] [Crossref]

20. World Bank. (2025). Digital development overview 2025. World Bank Group. https://www.worldbank.org [Google Scholar] [Crossref]

21. World Economic Forum. (2025). Future of jobs report 2025. World Economic Forum. https://www.weforum.org [Google Scholar] [Crossref]

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