Artificial intelligence in postgraduate education: Perceptions, practices, and ethical challenges in university management
This study used a hybrid approach to analyze the impact of artificial intelligence (AI) on graduate education management at private universities in the Lima metropolitan area. Data collection methods included semi-structured interviews with eight academic coordinators and questionnaires distributed to 40 professors and 200 graduate students from four private universities. The results showed that AI-based tools can support personalized learning, improve academic planning, and promote more informed decision-making. However, significant deficiencies remain in terms of technological infrastructure, systematic faculty training, and ethical guidance. The application of AI in graduate education management is still in its early stages, focusing primarily on administrative processes, student tracking, and automated data analysis, rather than pedagogical innovation. Qualitative findings highlight the crucial role of institutional leadership in fostering innovation, professional development, and ethical awareness. The study concludes that the effective implementation of AI depends on a clear institutional framework, ongoing capacity-building measures, and explicit ethical guidelines. The adoption of AI is closely linked to the institutional environment, teacher involvement, and ethical principles, which together ensure the integration of reflection, accountability, and equity.
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