Agentic AI in Higher Education: A Low-Code Framework for Administrative Automation and Strategic Oversight | ||
| المجلة العربية للإدارة | ||
| Articles in Press, Accepted Manuscript, Available Online from 08 September 2025 PDF (638.87 K) | ||
| Document Type: بحوث باللغة الإنجلیزیة | ||
| DOI: 10.21608/aja.2025.409429.1909 | ||
| Authors | ||
| Hossam Mohamed khamis Mohamed Daoud* ; Aiman Ahmed Ragab; Mohamed Abd El Salam Ragheb; Passent Tantawi | ||
| Arab Academy for Science, Technology and Maritime Transport | ||
| Abstract | ||
| A modularized, low-code automation system that follows the premise of the Agentic Artificial Intelligence (AI) internally known as Laila AI has been proposed in this paper which was completely designed, implemented and tested at the Graduate School of Business (GSB), Arab Academy for Science, Technology and Maritime Transport. Laila AI is self-generating, customizing, and real-time academic administrative workflow system with a dynamic interpretation of institutional input systems (LMS /SIS) and stakeholder data. In the system, the layer of the human-in-the-loop control is also implemented to guarantee its transparency, ethical regulatory use, and local adjustability. It was a mixed-methods case study that employed the use of system performance logs and structural surveys (n = 375) in addition to interviews with various stakeholders. The results indicate a high level of efficiency in operation: a more than 50% decrease in the time of task accomplishment, and automation of up to 70% of the assessment processes. More than 80% of the time, academic leadership reacted to strategic alerts within 48 hours. Qualitative information resonated with perceived gain in fairness, explainability, and trust among the stakeholders. Override and justification features provided active involvement of human reviewers, which supported the ethical dimension of governance. The above-stated findings assert that Laila AI encompasses a dualistic model of governance putting together independent decision reasoning and in-built moral control. Being a transparent, ethically controlled distributed digital form of administration, it presents a model that can be transferred to resource-restricted establishment of higher learning in disparate working environments. | ||
| Keywords | ||
| Artificial Intelligence; Higher Education; Automation | ||
| References | ||
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