Reimagining Marketing Strategy in the Age of AI: Strategic Decision-Making, Competitive Advantage, and Market Adaptability
Keywords:
Artificial Intelligence Adoption, Marketing Strategy Innovation, Customer-Centricity, Personalization, Segmentation, Pricing Optimization, Market Turbulence, Dynamic Capabilities, Strategic FitAbstract
The focus of this study was to assess how artificial intelligence (AI) could contribute to making strategic marketing decisions concerning the new ways companies are going to develop innovative marketing strategies through customer centeredness, customization/personalization, segmentation and pricing optimization. Based on Strategic Fit Theory and Dynamic Capabilities Theory, this study predicted that using artificial intelligence would positively affect the way companies innovate their marketing strategies (Hypothesis 1), and that this positive effect would increase with higher levels of environmental turbulence (Hypothesis 2). The purpose of this study was to provide the basis for a conceptual model, describe the methodology used to test it by developing scenarios, collecting and analysing data, and offer some advice to managers who are facing more turbulent competitive environments than ever before. Moreover, this study adds to the existing body of literature by linking AI adoption with strategic marketing research, specifying market turbulence as a moderating variable between AI and innovative marketing strategies, and offering actionable information to management teams operating in rapidly changing competitive environments.
References
[1] Akbar, M. A. (2024). Customer-Centric Strategies: Navigating the Dynamics of Marketing Management for Competitive Advantage. Advances in Business & Industrial Marketing Research, 2(2), pp.96–109.
[2] Amin, M. R., Asbi, A., Sivakumaran, V. M., Kim, J., & Septiarini, E. (2025). Artificial Intelligence (AI) adoption in marketing strategies: Navigating the present and shaping the future business landscape. Social Sciences & Humanities Open, 12, 102048.
[3] Chatterjee, L. (2023). The environmental turbulence concept in marketing: A look at interpretation, measurement, empirical effects, and future research. Journal of Business Research. Advance online publication.
[4] Dubey, U. K. B., & Kothari, D. P. (2022). Research methodology: Techniques and trends. Chapman and Hall/CRC
Grewal, D., et al. (2024). How generative AI is shaping the future of marketing. Journal of the Academy of Marketing Science. Advance online publication.
[5] Haleem, A., et al. (2022). Artificial intelligence (AI) applications for marketing. Journal of Business Research, 154, 113–123. (Citation approximate; see journal for full details)
[6] Javed, H., et al. (2025). Innovative Pathways: Leveraging AI adoption and team innovativeness. Businesses, 5(3), 28.
[7] Kachouie, R. (2018). Dynamic marketing capabilities view on creating market change. Monash University Research Repository.
[8] Mahmood, G., Ditta, A., Ramzan, M., & Abbas, Z. (2024). Role of Artificial Intelligence (AI) Adoption and Digital Transformation in Enhancing Sustainable Business Performance: The Mediating Effect of Green Product Innovation. Journal of Accounting and Finance in Emerging Economies, 10(4), 3172.
[9] Manoharan, G., Ashtikkar, S. P., & Nivedha, M. (2024). Artificial intelligence in decision-making: Reinventing business strategies. In Generative AI for Transformational Management (pp. 25-50). IGI Global
[10] Marmon, S. (2025). AI Business Strategy: How Generative Models Are Reshaping Competitive Advantage. Available at SSRN 5233756
[11] Subba Narasimha, P., & Erasmus, P. (2001). Strategy in turbulent environments: The role of dynamic competence. Long Range Planning, 34(3), pp.297–313.
[12] Saharan, V. A., Kulhari, H., Jadhav, H., Pooja, D., Banerjee, S., & Singh, A. (2024). Introduction to research methodology. In Principles of research methodology and ethics in pharmaceutical sciences (pp. 1-46). CRC Press
Tuominen, S. (2023). Customer-centric strategy driving innovativeness and competitiveness. Industrial Marketing Management, 40(3), pp.479–493.
[13] Walliman, N. (2021). Research methods: The basics. Routledge
[14] Zhang, C. X. (2021). The relationship between dynamic capabilities and marketing capabilities: Evidence from Chinese firms. Journal of Business & Industrial Marketing.
[15] Zhinuk, F., Sholomer, A., AHMED, M. S., & Sarkar, S. (2025). Adaptive AI-Powered Decision Support Systems for Strategic Business Management in Uncertain Markets. Journal of Computer Science and Technology Studies, 7(8), pp.161-171
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