This study proposes a conceptual model that explains the influence of leadership on the relationship between human intelligence (HI) and artificial intelligence (AI). A qualitative, non-systematic literature review was conducted in Scopus and Web of Science of the literature published in the last 5 years, using Boolean combinations of the terms “leadership,” “artificial intelligence,” and “human intelligence.” The thematic analysis allowed the identification of conceptual patterns and research gaps; the model elaborated from the review shows that leadership has an ethical and strategic mediation in the HI-AI relationship in a hybrid space of cooperation, in which automated decisions are put in real context through human judgment and reasoning; ethical governance mechanisms emerge for systems supported by artificial intelligence; and finally, a balancing mechanism to algorithmic efficiency is established through cognitive adaptability. The proposed framework offers organizations some guidelines for human supervision processes for AI-supported systems that integrate ethical evaluations into automated processes. It proposes elements—leadership tools that enhance the relationship between human intelligence and artificial intelligence. This article contributes to the management of organizations by proposing a model that recognizes leadership as a dynamic facilitator between HI and AI, integrating transdisciplinary knowledge of management, technological ethics, and cognitive science, and proposing an ethical interrelationship in the decision-making architectures between HI and AI. The proposed model establishes leadership mediation of human–AI interaction through four axes showing how leadership acts as the axis that brings together human and technological systems to work together. Hierarchical interaction creates a hybrid interaction that is highly flexible, efficient, and has ethical oversight. Finally, the proposed model is an open system that interacts with the environment and is understood as a flexible tool to support strategic decision-making in complex environments.

This paper aims to develop and provide the validity and reliability of a measurement scale that establishes the relationship between Leadership and Human–AI Collaboration. An instrumental study was conducted to inform the design and revision of a scale’s psychometric properties. The techniques used for statistical analysis were carried out in three sequences, namely, the first consisted of collecting validity evidence based on test content; the second consisted of an exploratory and confirmatory factor analysis to gather validity evidence based on internal structure; and the third consisted of estimating the test reliability of internal consistency through the omega coefficient. The results show that the proposed measurement scale meets the psychometric properties required of a social-science instrument.