P.E.N.S.A. FRAMEWORK: A METHODOLOGICAL PROPOSITION FOR AI-MEDIATED EXECUTIVE EDUCATION.

Authors

  • Alexandre Caramelo Pinto Fundação Getulio Vargas (FGV) - Instituto de Desenvolvimento Educacional
  • Caio Flávio Stettiner Fundação Getulio Vargas (FGV) - Instituto de Desenvolvimento Educacional
  • Enos Luiz da Silva Correa Fundação Getulio Vargas (FGV) – Instituto de Desenvolvimento Educacional
  • Fernando Pedro de Moraes Fundação Getulio Vargas (FGV) – Instituto de Desenvolvimento Educacional

DOI:

https://doi.org/10.24325/issn.2446-5763.v12i35p95-191

Keywords:

Generative Artificial Intelligence, Executive Education, Active Learning Methodologies, Experiential Learning, P.E.N.S.A. Framework

Abstract

The expansion of Generative Artificial Intelligence (GenAI) is transforming how organizations create knowledge, analyze information, and support decision-making processes, posing new challenges for executive and leadership development. Although the literature provides relevant contributions on Artificial Intelligence in education, active learning methodologies, Problem-Based Learning, and experiential learning, methodological approaches specifically designed to integrate these elements within Executive Education contexts remain relatively limited. To address this gap, this article introduces the concept of Executive AI Learning and proposes the P.E.N.S.A. Framework — Provoke, Explore, Navigate, Solve, and Learn —, a methodological proposition designed to structure learning experiences centered on organizational problems and mediated by Artificial Intelligence. The study adopts a qualitative, theoretical-propositional, and conceptual approach, grounded in an interdisciplinary literature review and the synthesis of theoretical perspectives related to Problem-Based Learning, the Case Method, Experiential Learning, Reflective Practice, Organizational Learning, and Artificial Intelligence as a cognitive technology. The framework organizes executive learning into five interdependent stages, explicitly defining the roles of instructors, participants, and AI, while incorporating intermediate artifacts that support the progression from problem framing to decision-making and from decision-making to learning. Its operationalization is illustrated through five fictional executive cases designed to represent different organizational challenges, without claiming empirical validation at this stage of the research. The study contributes by integrating and operationalizing established pedagogical foundations within a methodological architecture designed for AI-mediated Executive Education. As a theoretical-methodological proposition, the P.E.N.S.A. Framework provides a conceptual and operational foundation for application and adaptation, while establishing a basis for future empirical investigations into its effects in MBA programs, Corporate Education, and leadership developmen.

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Published

2026-09-03

How to Cite

Caramelo Pinto, A., Stettiner, C. F., da Silva Correa, E. L., & de Moraes, F. P. (2026). P.E.N.S.A. FRAMEWORK: A METHODOLOGICAL PROPOSITION FOR AI-MEDIATED EXECUTIVE EDUCATION. South American Development Society Journal, 12(35), 95. https://doi.org/10.24325/issn.2446-5763.v12i35p95-191

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