Adoption of artificial intelligence in decision-making processes and effects on organizational performance: a systematic review and a conceptual framework

Résumé

Abstract

Organizational performance increasingly depends on organizations’ ability to integrate advanced technologies that support strategic decision-making. In this context, artificial intelligence is emerging as a significant catalyst of transformation, particularly in environments characterized by uncertainty, competitive pressure, and rapid digital development. Although previous work confirms the positive effects of AI on decision-making quality and organizational outcomes, the literature remains fragmented regarding the mechanisms linking its adoption, the reconfiguration of decision-making processes, and performance improvement. In this context, this systematic review synthesizes the results from a selection of articles in order to provide an integrated understanding of AI adoption in an organizational context. On this basis, a conceptual model is developed to explain the mechanisms by which the adoption of AI influences decision-making processes, and show how this transformation translates into organizational performance.

Keywords: Artificial intelligence, adoption, decision-making process, organizational performance, organizational capabilities.