ARTIFICIAL INTELLIGENCE AND REIMAGINING OF PRODUCT COMPETITIVENESS: AN ANALYSIS OF EMERGING DETERMINANTS

Purpose. The primary objective of this research is to identify, classify, and analyze the emerging AI-driven factors that determine product competitiveness in the digital era. The study specifically explores how AI integration – through mechanisms such as deep personalization, real-time adaptability, and autonomous optimization – creates a new paradigm for achieving competitive advantage. It also develops strategic recommendations for firms seeking to enhance their market positions. Design/Methodology/Approach. A comprehensive review of academic literature, industry reports, and case studies forms the backbone of this research. The study utilizes theoretical generalization and comparative analysis to juxtapose traditional competitiveness factors with those emerging from AI applications. Comparative analysis is applied to group and structure new factors based on shared characteristics and interdependencies. This multidimensional methodology enables a holistic understanding of the cumulative impact of AI on product competitiveness. Findings. The findings reveal that AI integration fundamentally transforms the competitive landscape by shifting the focus from static attributes to dynamic, data-driven capabilities. The study demonstrates that AI enables products to achieve deep personalization and real-time adaptability, as algorithms continuously analyze consumer behavior and market trends to tailor products and services instantly. This capability not only enhances customer experiences but also builds stronger loyalty and trust. Moreover, the research highlights that AI-driven automation and predictive analytics significantly reduce operational costs while accelerating decision-making processes, thereby enabling companies to respond swiftly to market fluctuations. In addition, the integration of products into broader digital ecosystems – where products, services, and platforms interconnect – creates synergistic benefits that reinforce overall competitive strength. Generative AI, in particular, emerges as a catalyst for rapid innovation, facilitating the development of new products and services at unprecedented speeds. In emerging markets, such as those in Ukraine, companies that have embraced AI report enhanced resilience and market performance despite challenges such as limited digital infrastructure and skills shortages. Collectively, these insights suggest that traditional competitive dimensions are evolving into a dynamic interplay of technology, data analytics, and customer-centric innovation, establishing a robust framework for sustainable competitive advantage. Practical Implications. The insights from this study offer actionable strategies for businesses aiming to harness AI for competitive advantage. Companies are encouraged to invest in AI-driven technologies that enable personalized customer engagement and adaptive product design while developing integrated digital ecosystems that foster seamless interaction among products, services, and users. Embracing automation to streamline operations and enhance decision-making processes can further reduce inefficiencies and support proactive market strategies. Originality/Value. This research contributes a novel framework for understanding product competitiveness in the AI era by systematically identifying and categorizing new competitive factors. Unlike traditional models that focus solely on static attributes, the proposed approach highlights the dynamic interplay of technology, data, and customer experience. This integrative model bridges existing research gaps and provides a strategic roadmap for businesses navigating the transformative digital economy.