Mapping the Role of Generative AI in Reducing Administrative Workload in Higher Education: A Task-Centred Analysis

Ing. Iqra Mehmood

Diplomová práce

Anotace:

Artificial Intelligence is at the forefront of technological advancements and has seeped into every industry. However, one of the most overlooked instances remains within administrative departments within HEIs. These administrative tasks include day-to-day management of staff and students through processes that have long remained manual. This research explores several aspects of Generative AI, specifically examining how GEN AI reduces administrative workloads in HEIS. The research also goes a step further to identify which admin tasks are most affected using GEN AI tools. Additionally, the research produces a framework that shows which AI tools are best suited to different types of tasks, a finding widely scattered across the existing literature. The research has used a multiple-case study approach to data collection, involving both primary and secondary sources. The primary sources include policy briefings, white papers, and case studies published by reputable universities worldwide. The secondary papers include recently published studies on the subject matter from several reputable databases. The findings show that GenAI is particularly useful for tasks such as compliance validation, quiz generation, and document handling. The findings suggest that workload reduction depends on matching the right AI tool to the right administrative task. ChatGPT-style tools are useful for drafting, summarising, and preparing feedback. LMS-based AI tools are useful for preparing quizzes and assessments. RAG chatbots are useful for student services and policy queries when their knowledge bases are controlled. AI validation tools are useful for compliance checks, contract review, and reporting. However, tasks that require judgment, interpretation, or final approval still need human oversight.

Abstract:

Artificial Intelligence is at the forefront of technological advancements and has seeped into every industry. However, one of the most overlooked instances remains within administrative departments within HEIs. These administrative tasks include day-to-day management of staff and students through processes that have long remained manual. This research explores several aspects of Generative AI, specifically examining how GEN AI reduces administrative workloads in HEIS. The research also goes a step further to identify which admin tasks are most affected using GEN AI tools. Additionally, the research produces a framework that shows which AI tools are best suited to different types of tasks, a finding widely scattered across the existing literature. The research has used a multiple-case study approach to data collection, involving both primary and secondary sources. The primary sources include policy briefings, white papers, and case studies published by reputable universities worldwide. The secondary papers include recently published studies on the subject matter from several reputable databases. The findings show that GenAI is particularly useful for tasks such as compliance validation, quiz generation, and document handling. The findings suggest that workload reduction depends on matching the right AI tool to the right administrative task. ChatGPT-style tools are useful for drafting, summarising, and preparing feedback. LMS-based AI tools are useful for preparing quizzes and assessments. RAG chatbots are useful for student services and policy queries when their knowledge bases are controlled. AI validation tools are useful for compliance checks, contract review, and reporting. However, tasks that require judgment, interpretation, or final approval still need human oversight.

Keywords

GEN AI, Admin Workload, Higher Education Institute, Organisational Readiness, AI Adoption

Jazyk práce: angličtina

Datum vytvoření / odevzdání či podání práce: 11. 5. 2026

Obhajoba závěrečné práce

• Obhajoba proběhla 18. 6. 2026
• Vedoucí: doc. Ahad Zareravasan, PhD
• Oponent: PhD Seyed Mojtaba Hosseini Bamakan

Masarykova univerzita

Ekonomicko-správní fakulta

Magisterský studijní program / obor:
Business Management / Business Management