Exploring the Reconstruction of the Micro foundations of Dynamic Capabilities in the Age of Artificial Intelligence

HRMARS - By analyzing how AI alters the sensing, seizing, and reconfiguring processes, this study rethinks the micro-foundations of dynamic capabilities (DC) in the era of artificial intelligence. The emergence of AI introduces new actors, mechanisms, and decision logics that drastically change how businesses perceive their surroundings and react to change. Traditional Dynamic Capabilities theory is based on human cognition, routines, and experiential judgment. This study creates a hybrid framework with hybrid actors, algorithmic mechanisms, and hybrid decision logic based on dynamic capability theory, organizational information processing, human–AI collaboration, and algorithmic agency research. The analysis demonstrates that AI is an emerging meta-capability that increases the scope and speed of environmental sensing, rather than just a technical tool, accelerates resource reconfiguration through automation and digital replication and improves strategic seizing through simulation, prediction, and optimization. These changes result in a hybrid human-AI configuration rather than a human-centric model for capability formation. Empirical research is necessary as a conceptual study to verify the suggested claims and investigate cross-industry variations and the dynamics of human–AI interaction. Practically, firms must redesign their sensing, decision-making, and reconfiguration systems to integrate AI, while managers need new competencies in orchestrating human–AI collaboration and overseeing algorithmic governance. This study provides one of the earliest systematic frameworks for understanding how AI reshapes the micro foundations of dynamic capabilities and offers a new theoretical lens for explaining enterprise evolution in the AI era.