Artificial intelligence (AI) advances and the rapid adoption of generative AI tools like ChatGPT present new opportunities and challenges for higher education. While substantial literature discusses AI in higher education, there is a lack of a systemic approach that captures a holistic view of the AI transformation of higher education institutions (HEIs). To fill this gap, this article, taking a complex systems approach, develops a causal loop diagram (CLD) to map the causal feedback mechanisms of AI transformation in a typical HEI. Our model accounts for the forces that drive the AI transformation and the consequences of the AI transformation on value creation in a typical HEI. The article identifies and analyzes several reinforcing and balancing feedback loops, showing how, motivated by AI technology advances, the HEI invests in AI to improve student learning, research, and administration. The HEI must take measures to deal with academic integrity problems and adapt to changes in available jobs due to AI, emphasizing AI-complementary skills for its students. However, HEIs face a competitive threat and several policy traps that may lead to decline. HEI leaders need to become systems thinkers to manage the complexity of the AI transformation and benefit from the AI feedback loops while avoiding the associated pitfalls. We also discuss long-term scenarios, the notion of HEIs influencing the direction of AI, and directions for future research on AI transformation.

翻译：人工智能（AI）的进步以及ChatGPT等生成式AI工具的快速普及为高等教育带来了新的机遇与挑战。尽管已有大量文献探讨AI在高等教育中的应用，但缺乏从系统角度全面把握高等教育机构（HEIs）AI转型的综合性研究。为填补这一空白，本文采用复杂系统方法，开发了一个因果循环图（CLD），用以描绘典型HEI中AI转型的因果反馈机制。我们的模型考虑了驱动AI转型的力量，以及AI转型对典型HEI价值创造的影响。本文识别并分析了多个增强型和平衡型反馈回路，展示了在AI技术进步驱动下，HEI如何通过投资AI来改善学生学习、科研和行政管理。HEI必须采取措施应对学术诚信问题，并适应AI带来的就业变化，强调培养学生掌握AI互补技能。然而，HEI面临竞争威胁和若干政策陷阱，可能导致其衰落。HEI领导者需要成为系统思考者，以管理AI转型的复杂性，在利用AI反馈回路的同时避免相关风险。我们还讨论了长期情景、HEI影响AI发展方向的概念，以及未来AI转型研究的潜在方向。