Background. Business Simulation Games (BSG) are widely used to foster experiential learning in complex managerial and organisational contexts by exposing students to decision-making under uncertainty. In parallel, Artificial Intelligence (AI) is increasingly integrated into higher education to support learning activities. However, despite growing interest of AI in education, its specific role in BSG and its implications for knowledge creation processes remain under-theorised. Intervention. This paper reports on the integration of generative AI tools into a BSG designed for engineering students. AI was embedded as a support mechanism during the simulation to assist students in analysing events, reformulating information, and generating decision-relevant insights, while instructors retained responsibility for supervision, debriefing, and complex issues. Methods. Adopting a qualitative experience-report approach, the study draws on the SECI model (Socialisation, Externalisation, Combination, Internalisation) as an analytical framework to examine how students and instructors interacted with AI during the simulation and how different forms of knowledge were mobilised and developed. Results. The findings indicate that AI primarily supports the Combination phase of the SECI model by facilitating the rapid synthesis, reformulation, and contextualisation of explicit knowledge. In contrast, the processes of Socialisation, Externalisation, and Internalisation remained largely dependent on peer interaction, individual reflection, and instructor guidance. Discussion. The results suggest a functional boundary in human-AI collaboration within simulation-based learning. AI acts as a cognitive enhancer that improves responsiveness and access to explicit knowledge, but it does not replace the pedagogical role of instructors in supporting the development of tacit knowledge, competencies, and phronesis. Conclusion. Integrating AI into BSG can enhance learning efficiency and engagement, but effective experiential learning continues to rely on active human supervision. Future research should investigate instructional designs that better support tacit knowledge acquisition in AI-assisted simulations.

翻译：背景。商业模拟游戏（BSG）通过让学生在不确定性下进行决策，被广泛用于促进复杂管理和组织情境中的体验式学习。与此同时，人工智能（AI）正日益融入高等教育以支持学习活动。然而，尽管AI在教育领域的兴趣日益增长，其在BSG中的具体作用及其对知识创造过程的影响仍缺乏充分的理论探讨。干预措施。本文报告了将生成式AI工具集成到为工程专业学生设计的BSG中的实践。AI被嵌入作为模拟过程中的支持机制，协助学生分析事件、重构信息并生成与决策相关的见解，而教师则保留监督、汇报和解决复杂问题的职责。方法。本研究采用定性经验报告方法，借鉴SECI模型（社会化、外化、组合化、内化）作为分析框架，考察学生和教师在模拟过程中如何与AI互动，以及不同形式的知识如何被调动和发展。结果。研究结果表明，AI主要通过促进显性知识的快速综合、重构和情境化，来支持SECI模型的组合化阶段。相比之下，社会化、外化和内化过程仍然在很大程度上依赖于同伴互动、个人反思和教师指导。讨论。研究结果揭示了基于模拟的学习中人与AI协作的功能边界。AI作为一种认知增强器，提高了响应能力和对显性知识的获取，但它并未取代教师在支持隐性知识、能力和实践智慧发展方面的教学作用。结论。将AI集成到BSG中可以提升学习效率和参与度，但有效的体验式学习仍然依赖于积极的人工监督。未来的研究应探索能更好地支持AI辅助模拟中隐性知识获取的教学设计。