In the contemporary digital landscape, organizations increasingly adopt Artificial Intelligence (AI) to secure a sustainable competitive advantage. However, empirical evidence suggests that technology adoption alone is insufficient to guarantee long-term performance. Instead, the strategic integration of AI workflows by embedding AI into core organizational processes has emerged as a critical driver for competitive value. Simultaneously, the dynamic capabilities perspective emphasizes a firm’s capacity to identify opportunities, adapt to environmental shifts and reconfigure resources. While research links AI to these capabilities, the specific mechanisms of this relationship in digital businesses within emerging economies remain underexplored. This study, therefore, investigates the mediating role of organizational dynamic capabilities in the relationship between AI workflow integration and sustainable competitive advantage.

This research utilizes an applied, quantitative, and correlational-analytical approach. The statistical population consists of managers and decision-makers in Iranian digital businesses with practical experience in AI application. Due to the specialized nature of the population, we employed a non-probability purposive sampling method, gathering 250 valid responses through a researcher-developed, five-point Likert scale questionnaire. We validated the instrument’s content and reliability through expert review and subsequently analyzed the research hypotheses using Structural Equation Modeling with Partial Least Squares (PLS-SEM) in SmartPLS, a method well-suited for predictive modeling and complex data structures.

The findings indicate that AI workflow integration has a positive and significant effect on both organizational dynamic capabilities and sustainable competitive advantage. Most importantly, the analysis confirms the mediating role of dynamic capabilities, suggesting that AI-driven workflows enhance competitive advantage not only directly but also indirectly by strengthening a firm’s capacity to sense opportunities, adapt to environmental volatility, and reconfigure resources effectively.

In conclusion, gaining access to advanced AI is no longer enough to ensure long-term competitiveness. Firms must embed these technologies into their organizational routines and leverage them through dynamic capabilities. This study contributes to the literature by introducing an integrated model that elucidates how AI creates value through organizational mechanisms rather than solely through technological effects. The results provide practical implications for managers and policymakers, suggesting that digital businesses should prioritize the development of dynamic capabilities such as fostering organizational learning, promoting data-driven decision-making, and ensuring flexible resource allocation alongside their investments in AI. By aligning AI initiatives with these internal organizational mechanisms, firms in emerging economies can bolster their resilience and secure a sustainable competitive position in increasingly dynamic and aggressive markets.