2.5

CiteScore

8.8

Global Impact Factor

Beyond automation: Arts-based learning and the 4A model for human capability development in the generative AI era


Paper ID: EIJTEM_2026_13_3_6-16

Author's Name: Dr. Ignacio Bonasa Alzuria

Volume: 13

Issue: 3

Year: 2026

Page No: 6-16

Abstract:

Generative artificial intelligence can improve the speed and apparent quality of cognitive work, but polished output may coexist with shallow comprehension, dependence, homogenised ideas and weakened authorship. This conceptual study develops the 4A model as a human capability architecture for management learning in the generative AI era. A structured integrative review connects arts-based management development, experiential and transformative learning, cognitive offloading, self-determination theory, psychological safety, creativity research and human-AI interaction. The model comprises Aprendizaje (Learning), Actitud (Attitude), Alma (Soul) and Acción (Action). The Spanish terms preserve the original four-A architecture; operationally, they denote authored understanding, adaptive disposition, ethical-relational meaning and responsible behavioural transfer. Arts-based experience is positioned as a transversal medium that expands perception, embodiment, ambiguity tolerance and perspective-taking. AI is positioned as a bounded collaborator that may explain, compare, simulate, challenge and organise feedback, but may not replace first-person judgement, relational recognition or moral accountability. The article specifies eight falsifiable propositions, boundary conditions, design principles, a four-phase learning cycle, a multidimensional assessment rubric and a staged validation programme. Its distinctive contribution is a non-compensatory integration of cognition, disposition, meaning and action: technical fluency alone is insufficient when it does not preserve epistemic agency, ethical coherence and real-world responsibility. The framework offers universities, executive educators and organisational learning teams a practical and testable basis for human-AI learning design.

Keywords: Generative artificial intelligence; arts-based learning; management development; 4A model; human capabilities; creativity; ethical leadership; experiential learning.

References:

Amershi, S., Weld, D., Vorvoreanu, M., Fourney, A., Nushi, B., Collisson, P., Suh, J., Iqbal, S., Bennett, P. N., Inkpen, K., Teevan, J., Kikin-Gil, R., & Horvitz, E. (2019). Guidelines for human-AI interaction. Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, 1–13. https://doi.org/10.1145/3290605.3300233
Barry, D., & Meisiek, S. (2010). Seeing more and seeing differently: Sensemaking, mindfulness, and the workarts. Organization Studies, 31(11), 1505–1530. https://doi.org/10.1177/0170840610380802
Barsalou, L. W. (2008). Grounded cognition. Annual Review of Psychology, 59, 617–645. https://doi.org/10.1146/annurev.psych.59.103006.093639
Brynjolfsson, E., Li, D., & Raymond, L. R. (2025). Generative AI at work. The Quarterly Journal of Economics, 140(2), 889–942. https://doi.org/10.1093/qje/qjae044
Csikszentmihalyi, M. (1996). Creativity: Flow and the psychology of discovery and invention. HarperCollins.
Deci, E. L., & Ryan, R. M. (2000). The ‘what’ and ‘why’ of goal pursuits: Human needs and the self-determination of behavior. Psychological Inquiry, 11(4), 227–268. https://doi.org/10.1207/S15327965PLI1104_01
Doshi, A. R., & Hauser, O. P. (2024). Generative AI enhances individual creativity but reduces the collective diversity of novel content. Science Advances, 10(28), eadn5290. https://doi.org/10.1126/sciadv.adn5290
Edmondson, A. (1999). Psychological safety and learning behavior in work teams. Administrative Science Quarterly, 44(2), 350–383. https://doi.org/10.2307/2666999
Eisner, E. W. (2002). The arts and the creation of mind. Yale University Press.
Fiorella, L., & Mayer, R. E. (2015). Learning as a generative activity: Eight learning strategies that promote understanding. Cambridge University Press.
Gibb, S. (2004). Arts-based training in management development: The use of improvisational theatre. Journal of Management Development, 23(8), 741–750. https://doi.org/10.1108/02621710410549594
Glăveanu, V. P. (2015). Creativity as a sociocultural act. The Journal of Creative Behavior, 49(3), 165–180. https://doi.org/10.1002/jocb.94
Kapur, M. (2008). Productive failure. Cognition and Instruction, 26(3), 379–424. https://doi.org/10.1080/07370000802212669
Kolb, D. A. (1984). Experiential learning: Experience as the source of learning and development. Prentice Hall.
Long, D., & Magerko, B. (2020). What is AI literacy? Competencies and design considerations. Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems, 1–16. https://doi.org/10.1145/3313831.3376727
Mezirow, J. (1991). Transformative dimensions of adult learning. Jossey-Bass.
Nissley, N. (2010). Arts-based learning at work: Economic downturns, innovation upturns, and the eminent practicality of arts in business. Journal of Business Strategy, 31(4), 8–20. https://doi.org/10.1108/02756661011055140
Noy, S., & Zhang, W. (2023). Experimental evidence on the productivity effects of generative artificial intelligence. Science, 381(6654), 187–192. https://doi.org/10.1126/science.adh2586
OECD. (2019). OECD Future of Education and Skills 2030: OECD Learning Compass 2030. OECD Publishing. https://www.oecd.org/education/2030-project/teaching-and-learning/learning/
Risko, E. F., & Gilbert, S. J. (2016). Cognitive offloading. Trends in Cognitive Sciences, 20(9), 676–688. https://doi.org/10.1016/j.tics.2016.07.002
Rosso, B. D., Dekas, K. H., & Wrzesniewski, A. (2010). On the meaning of work: A theoretical integration and review. Research in Organizational Behavior, 30, 91–127. https://doi.org/10.1016/j.riob.2010.09.001
Runco, M. A., & Jaeger, G. J. (2012). The standard definition of creativity. Creativity Research Journal, 24(1), 92–96. https://doi.org/10.1080/10400419.2012.650092
Sawyer, R. K. (2012). Explaining creativity: The science of human innovation (2nd ed.). Oxford University Press.
Schön, D. A. (1983). The reflective practitioner: How professionals think in action. Basic Books.
Snyder, H. (2019). Literature review as a research methodology: An overview and guidelines. Journal of Business Research, 104, 333–339. https://doi.org/10.1016/j.jbusres.2019.07.039
Taylor, S. S., & Ladkin, D. (2009). Understanding arts-based methods in managerial development. Academy of Management Learning & Education, 8(1), 55–69. https://doi.org/10.5465/AMLE.2009.37012179
Torraco, R. J. (2005). Writing integrative literature reviews: Guidelines and examples. Human Resource Development Review, 4(3), 356–367. https://doi.org/10.1177/1534484305278283
UNESCO. (2023). Guidance for generative AI in education and research. UNESCO. https://unesdoc.unesco.org/ark:/48223/pf0000386693
UNESCO. (2024). AI competency framework for students. UNESCO. https://unesdoc.unesco.org/ark:/48223/pf0000391105
UNESCO. (2024). AI competency framework for teachers. UNESCO. https://unesdoc.unesco.org/ark:/48223/pf0000391104
Wenger, E. (1998). Communities of practice: Learning, meaning, and identity. Cambridge University Press.

View PDF