This study examines the intellectual structure of research connecting artificial intelligence (AI) and dynamic capabilities and explains how AI strengthens organizational sensing, seizing, and transforming to promote agility, value creation, and sustained competitive advantage.
Existing research often treats AI as a technological resource and remains fragmented across strategy, innovation, and information-systems domains. This study reconceptualizes AI as a capability-enabling mechanism and integrates these streams into a unified strategic framework and future research agenda.
A bibliometric review examined 213 peer-reviewed Web of Science management articles published between 2018 and 2025. Co-citation analysis of the 25 most influential publications used Ochiai-normalized coefficients and multidimensional scaling to map the field’s intellectual structure and research clusters.
Seven research clusters emerged, spanning digital strategy, core dynamic capabilities, agile sensing and seizing, AI-enabled services, AI microfoundations, ecosystems and value creation, and knowledge and innovation. AI creates advantage by enabling, rather than independently constituting, dynamic capabilities.
The study integrates contextual drivers, AI-enabled microfoundations, sensing–seizing–transforming processes, and strategic outcomes within one framework. It extends dynamic capabilities theory by specifying AI’s enabling mechanisms and demonstrates how bibliometric mapping can consolidate a fragmented interdisciplinary knowledge base.
Managers should embed AI within decision routines, organizational learning, resource allocation, business-model renewal, and ecosystem collaboration rather than pursue isolated technology investments. The framework helps leaders align AI initiatives with adaptability, responsible human–AI coordination, innovation, and durable value creation.