Designing AI-Agent-Enabled Entrepreneurship Training Programs: An Experiential Learning Approach to Business Automation, Opportunity Recognition, and Entrepreneurial Decision-Making
DOI:
https://doi.org/10.63282/3117-5481/AIJCST-V8I5P102Keywords:
AI Agents, Entrepreneurship Education, Experiential Learning, Business Automation, Opportunity Recognition, Entrepreneurial Decision-Making, Human-AI CollaborationAbstract
Entrepreneurship education increasingly employs generative artificial intelligence, yet proficiency in prompting a chatbot does not necessarily prepare learners to design accountable AI-agent workflows or make defensible business decisions. This article develops an experiential training framework that integrates opportunity recognition, business process automation, and entrepreneurial decision-making within a human-governed AI-agent environment. Using a theory-informed conceptual design approach, the framework synthesizes experiential learning, entrepreneurship-as-practice, effectuation, entrepreneurial competence, AI literacy, and responsible AI governance. It specifies six learner competencies, an eight-week studio curriculum, three interconnected practice strands, and a repeatable cycle of experience, reflection, conceptualization, and bounded experimentation. Learners are asked to interrogate market claims, compare alternative venture actions, prototype low-risk automations, and document why they accept or reject agent recommendations. An agent architecture separates information retrieval and proposed actions from human authorization and outcome verification. The article also proposes observable performance measures, assessment rubrics, and a future comparative evaluation design for estimating competency gains without conflating task completion with entrepreneurial learning. The principal contribution is a practical and testable instructional design that connects technological capability with entrepreneurial judgment. Its effectiveness remains a proposition to be examined through implementation and empirical assessment rather than an established result. The framework is intended for higher education, incubators, and professional entrepreneurship programmes with varied levels of technical preparation.
References
[1] Ahmad, A., Amry, D., Oakley, D., McInerny, J., & Napitupulu, M. (2026). AI as intern, not oracle: A design logic for human-AI partnership in experiential entrepreneurship education. Entrepreneurship Education. https://doi.org/10.1007/s41959-026-00196-7
[2] Autio, C., Schwartz, R., Dunietz, J., Jain, S., Stanley, M., Tabassi, E., Hall, P., & Roberts, K. (2024). Artificial intelligence risk management framework: Generative artificial intelligence profile (NIST AI 600-1). National Institute of Standards and Technology. https://doi.org/10.6028/NIST.AI.600-1
[3] Bacigalupo, M., Kampylis, P., Punie, Y., & Van den Brande, G. (2016). EntreComp: The entrepreneurship competence framework (EUR 27939 EN). Publications Office of the European Union. https://doi.org/10.2791/593884
[4] Baron, R. A. (2006). Opportunity recognition as pattern recognition: How entrepreneurs 'connect the dots' to identify new business opportunities. Academy of Management Perspectives, 20(1), 104–119. https://doi.org/10.5465/amp.2006.19873412
[5] Chandler, G. N., DeTienne, D. R., McKelvie, A., & Mumford, T. V. (2011). Causation and effectuation processes: A validation study. Journal of Business Venturing, 26(3), 375–390. https://doi.org/10.1016/j.jbusvent.2009.10.006
[6] Cope, J. (2005). Toward a dynamic learning perspective of entrepreneurship. Entrepreneurship Theory and Practice, 29(4), 373–397. https://doi.org/10.1111/j.1540-6520.2005.00090.x
[7] Darnell, J. A., & Gopalkrishnan, S. (2024). Entrepreneurship teaching exercises: Integrating generative AI. Discover Education, 3, Article 172. https://doi.org/10.1007/s44217-024-00261-0
[8] Davidsson, P. (2015). Entrepreneurial opportunities and the entrepreneurship nexus: A re-conceptualization. Journal of Business Venturing, 30(5), 674–695. https://doi.org/10.1016/j.jbusvent.2015.01.002
[9] DeTienne, D. R., & Chandler, G. N. (2004). Opportunity identification and its role in the entrepreneurial classroom: A pedagogical approach and empirical test. Academy of Management Learning & Education, 3(3), 242–257. https://doi.org/10.5465/amle.2004.14242103
[10] Duong, C. D., & Nguyen, T. H. (2024). How ChatGPT adoption stimulates digital entrepreneurship: A stimulus-organism-response perspective. The International Journal of Management Education, 22(3), Article 101019. https://doi.org/10.1016/j.ijme.2024.101019
[11] Hevner, A. R., March, S. T., Park, J., & Ram, S. (2004). Design science in information systems research. MIS Quarterly, 28(1), 75–105. https://doi.org/10.2307/25148625
[12] Hmelo-Silver, C. E. (2004). Problem-based learning: What and how do students learn? Educational Psychology Review, 16(3), 235–266. https://doi.org/10.1023/B:EDPR.0000034022.16470.f3
[13] Kolb, A. Y., & Kolb, D. A. (2005). Learning styles and learning spaces: Enhancing experiential learning in higher education. Academy of Management Learning & Education, 4(2), 193–212. https://doi.org/10.5465/amle.2005.17268566
[14] Kolb, D. A. (1984). Experiential learning: Experience as the source of learning and development. Prentice-Hall.
[15] Lo, C. K. (2023). What is the impact of ChatGPT on education? A rapid review of the literature. Education Sciences, 13(4), Article 410. https://doi.org/10.3390/educsci13040410
[16] Long, D., & Magerko, B. (2020). What is AI literacy? Competencies and design considerations. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems (pp. 1–16). Association for Computing Machinery. https://doi.org/10.1145/3313831.3376727
[17] McGee, J. E., Peterson, M., Mueller, S. L., & Sequeira, J. M. (2009). Entrepreneurial self-efficacy: Refining the measure. Entrepreneurship Theory and Practice, 33(4), 965–988. https://doi.org/10.1111/j.1540-6520.2009.00304.x
[18] McMullen, J. S., & Shepherd, D. A. (2006). Entrepreneurial action and the role of uncertainty in the theory of the entrepreneur. Academy of Management Review, 31(1), 132–152. https://doi.org/10.5465/amr.2006.19379628
[19] Miao, F., Shiohira, K., & Lao, N. (2024). AI competency framework for students. UNESCO. https://doi.org/10.54675/JKJB9835
[20] Nabi, G., Liñán, F., Fayolle, A., Krueger, N., & Walmsley, A. (2017). The impact of entrepreneurship education in higher education: A systematic review and research agenda. Academy of Management Learning & Education, 16(2), 277–299. https://doi.org/10.5465/amle.2015.0026
[21] Nambisan, S. (2017). Digital entrepreneurship: Toward a digital technology perspective of entrepreneurship. Entrepreneurship Theory and Practice, 41(6), 1029–1055. https://doi.org/10.1111/etap.12254
[22] Neck, H. M., & Greene, P. G. (2011). Entrepreneurship education: Known worlds and new frontiers. Journal of Small Business Management, 49(1), 55–70. https://doi.org/10.1111/j.1540-627X.2010.00314.x
[23] Neck, H. M., Greene, P. G., & Brush, C. G. (2014). Teaching entrepreneurship: A practice-based approach. Edward Elgar Publishing. https://doi.org/10.4337/9781782540564
[24] Ng, D. T. K., Leung, J. K. L., Chu, S. K. W., & Qiao, M. S. (2021). Conceptualizing AI literacy: An exploratory review. Computers and Education: Artificial Intelligence, 2, Article 100041. https://doi.org/10.1016/j.caeai.2021.100041
[25] Ouyang, F., & Jiao, P. (2021). Artificial intelligence in education: The three paradigms. Computers and Education: Artificial Intelligence, 2, Article 100020. https://doi.org/10.1016/j.caeai.2021.100020
[26] Park, J. S., O'Brien, J. C., Cai, C. J., Morris, M. R., Liang, P., & Bernstein, M. S. (2023). Generative agents: Interactive simulacra of human behavior. In Proceedings of the 36th Annual ACM Symposium on User Interface Software and Technology (Article 2, pp. 1–22). Association for Computing Machinery. https://doi.org/10.1145/3586183.3606763
[27] Pittaway, L., & Cope, J. (2007). Simulating entrepreneurial learning: Integrating experiential and collaborative approaches to learning. Management Learning, 38(2), 211–233. https://doi.org/10.1177/1350507607075776
[28] Renz, P. A., Martin, J., & Flad, M. (2025). Large language models as a catalyst for opportunity recognition capability. International Journal of Entrepreneurial Behavior & Research. https://doi.org/10.1108/IJEBR-08-2024-0815
[29] Sarasvathy, S. D. (2001). Causation and effectuation: Toward a theoretical shift from economic inevitability to entrepreneurial contingency. Academy of Management Review, 26(2), 243–263. https://doi.org/10.5465/amr.2001.4378020
[30] Shane, S., & Venkataraman, S. (2000). The promise of entrepreneurship as a field of research. Academy of Management Review, 25(1), 217–226. https://doi.org/10.5465/amr.2000.2791611
[31] Shinn, N., Cassano, F., Gopinath, A., Narasimhan, K., & Yao, S. (2023). Reflexion: Language agents with verbal reinforcement learning. Advances in Neural Information Processing Systems, 36, 8634–8652. https://doi.org/10.52202/075280-0377
[32] Triantoro, T., Rua, T., & Lang, G. (2025). AI skills for entrepreneurs: A practical experiential learning approach. Information Systems Education Journal, 23(3), 31–40. https://doi.org/10.62273/MLUM6680
[33] Vaccaro, M., Almaatouq, A., & Malone, T. (2024). When combinations of humans and AI are useful: A systematic review and meta-analysis. Nature Human Behaviour, 8, 2293–2303. https://doi.org/10.1038/s41562-024-02024-1
[34] Wang, L., Ma, C., Feng, X., Zhang, Z., Yang, H., Zhang, J., Chen, Z., Tang, J., Chen, X., Lin, Y., Zhao, W. X., Wei, Z., & Wen, J. (2024). A survey on large language model based autonomous agents. Frontiers of Computer Science, 18, Article 186345. https://doi.org/10.1007/s11704-024-40231-1
[35] Yao, S., Zhao, J., Yu, D., Du, N., Shafran, I., Narasimhan, K., & Cao, Y. (2023). ReAct: Synergizing reasoning and acting in language models. In The Eleventh International Conference on Learning Representations. https://openreview.net/forum?id=WE_vluYUL-X
