The Impact of Claude Agents and Autonomous AI Agents on Higher Education: Opportunities, Challenges, and Implications for Educational Leadership

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中文解读待补充：本站会优先为大语言模型、生成式AI、ChatGPT相关技术、计算机视觉、深度学习等高价值论文补充中文说明。

Original abstract

Artificial intelligence (AI) is rapidly evolving from conversational large language models (LLMs) toward Agentic AI, represented by autonomous AI agents capable of reasoning, planning, memory management, tool use, and autonomous workflow execution. While existing research has largely focused on the educational impact of generative AI systems such as ChatGPT, considerably less attention has been devoted to Claude Agents and other autonomous AI agents despite their growing potential to transform teaching, learning, research, academic administration, and institutional decision-making. This study addresses this emerging research gap by examining the opportunities, challenges, and leadership implications associated with the adoption of autonomous AI agents in higher education.The study employs a conceptual review with thematic literature analysis to synthesize recent interdisciplinary research on agentic AI, Human–AI Collaboration, educational leadership, AI governance, and higher education. The analysis identifies several opportunities, including personalized learning, intelligent tutoring, research assistance, curriculum development, administrative automation, and evidence-informed decision support. At the same time, the literature highlights important challenges related to academic integrity, hallucinations, transparency, algorithmic bias, privacy, cybersecurity, accountability, and the need for meaningful human oversight.The findings suggest that the successful integration of autonomous AI agents depends not only on technological capabilities but also on institutional readiness, effective governance, ethical frameworks, and visionary educational leadership. Rather than replacing educators or institutional leaders, Claude Agents and Autonomous AI Agents should be understood as intelligent collaborators that augment human expertise within a Human–AI Collaboration paradigm. By extending current discussions beyond conversational generative AI, this article contributes an integrated conceptual perspective linking agentic AI, institutional transformation, and educational leadership, while providing practical implications for universities preparing for the next generation of AI-enabled higher education.

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