Avaliação do impacto da maturidade em gestão da inteligência artificial no desempenho organizacional - Belchior Junior, Marcio André (2025)
This dissertation investigates how maturity in Artificial Intelligence (AI) management influences organizational performance in light of the Resource-Based View (RBV). Recognizing that technology alone does not ensure competitive advantage, the study analyzes: (i) the relationship between AI maturity and organizational capabilities; (ii) the influence of this maturity on organizational behavior in the use of resources; and (iii) the role of digital transformation as an antecedent of AI maturity. The proposed model was evaluated through structural equations, through ADANCO software, using data from 153 companies at different stages of digitalization. The findings show that AI maturity does not directly affect performance but strengthens it indirectly by enhancing internal capabilities and resource management practices. More mature organizations integrate technological, human, and structural resources in a coordinated manner, creating an environment conducive to innovation. Digital transformation proved to be a necessary condition for the development of this maturity, as it consolidates processes, policies, and governance that support the strategic use of AI. The study expands RBV literature by demonstrating that the effects of AI on performance depend on mediating mechanisms linked to capabilities and organizational behavior, reinforcing the need for systemic approaches in investigating technology as a strategic resource. From a managerial perspective, the results show that investing in technology alone is not enough. It is necessary to align AI initiatives with strategy, promote training, and cultivate a culture of continuous learning. Maturity in AI management enhances organizational performance when integrated with other internal elements.