GOVERNANCE MECHANISMS AND ELEMENTS FOR THE ADOPTION OF GENERATIVE ARTIFICIAL INTELLIGENCE IN BRAZILIAN UNIVERSITIES: PROPOSAL OF A CONCEPTUAL FRAMEWORK
Generative Artificial Intelligence; Generative AI Governance; Higher Education; Conceptual framework.
Generative Artificial Intelligence (GAI) has increasingly been recognized as a transformative force in higher education, offering benefits such as enhanced learning experiences and increased efficiency in academic research. However, a literature review revealed that significant challenges persist, including concerns about student data privacy, the spread of misinformation, and biases in evaluation processes. Furthermore, there is a notable scarcity of governance structures capable of effectively managing the ethical, regulatory, and operational impacts of GAI in higher education institutions. To address this gap, this study examines the corporate governance mechanisms and strategies adopted by Brazilian universities in implementing GAI and proposes a governance framework. This qualitative, inductive, exploratory, and descriptive research is operationalized through a scoping review, empirical data collection via active and passive transparency, and thematic analysis of institutional documents and reports. The study focuses on Brazilian universities ranked highest in at least one of the academic excellence rankings (Folha University Ranking 2024, QS World University Ranking 2025, and Times Higher Education World University Rankings 2025), based on the premise that these institutions tend to have established technological governance structures, making them relevant cases for analysis. The findings indicate that GAI governance adoption remains at an initial stage in top-ranked Brazilian universities, highlighting the urgent need for comprehensive governance frameworks to address ethical, regulatory, and strategic challenges. This research contributes to the field of organizational management by mapping the current state of GAI governance in leading Brazilian universities, proposing a structured framework for GAI implementation in higher education, and identifying effective corporate governance mechanisms for educational technologies.