Investigation into the Role of AI-Based Decision Support Systems in University Administrative Planning: A Case Study of Federal University, Lafia (Lafia LGA, Nasarawa State)
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Background of the Study
Effective administrative planning is critical to the smooth operation and growth of universities, encompassing tasks such as budgeting, resource allocation, scheduling, and decision-making. Traditional administrative systems often rely on manual processes and historical data, which can be inefficient, error-prone, and unable to respond to the dynamic needs of the university (Olatunji & Hassan, 2024). The advent of AI-based decision support systems (DSS) presents an opportunity to optimize administrative planning by providing data-driven insights, predictive analytics, and real-time decision-making capabilities (Ibrahim & Adamu, 2025). These systems use AI techniques such as machine learning, data mining, and optimization algorithms to assist university administrators in making informed decisions, thereby improving operational efficiency and institutional outcomes.
Federal University, Lafia, located in Lafia LGA, Nasarawa State, offers a valuable context for exploring the potential of AI-based DSS in university administration. The university, like many others in Nigeria, faces challenges related to resource allocation, budget management, and decision-making in a fast-paced, complex academic environment. This study aims to investigate the role of AI-based DSS in enhancing administrative planning at the university, focusing on the system's ability to improve efficiency and support data-driven decision-making processes.
Statement of the Problem
At Federal University, Lafia, administrative planning often relies on traditional methods that can be slow, reactive, and insufficiently flexible to adapt to changing needs. These inefficiencies can lead to delays in decision-making, poor resource allocation, and missed opportunities for optimization. While AI-based decision support systems have the potential to improve administrative processes, their implementation and effectiveness in Nigerian universities have not been fully explored.
Objectives of the Study
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To investigate the role of AI-based decision support systems in university administrative planning at Federal University, Lafia.
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To evaluate the effectiveness of AI-based DSS in improving efficiency and accuracy in administrative decision-making.
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To assess the impact of AI-based DSS on resource allocation and operational outcomes at the university.
Research Questions
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How can AI-based decision support systems improve administrative planning at Federal University, Lafia?
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What is the impact of AI-based DSS on the efficiency and accuracy of decision-making processes in university administration?
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How does the use of AI-based DSS affect resource allocation and operational outcomes at the university?
Significance of the Study
This study will offer valuable insights into how AI can transform university administrative processes, providing recommendations for the adoption of AI-based DSS in Nigerian universities. The findings could lead to more efficient, transparent, and data-driven decision-making at Federal University, Lafia and similar institutions.
Scope and Limitations of the Study
The study will focus on investigating the use of AI-based decision support systems in university administrative planning at Federal University, Lafia, located in Lafia LGA, Nasarawa State. The research will examine the system's impact on decision-making and resource allocation, excluding other aspects of university administration and external influences.
Definitions of Terms
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AI-Based Decision Support System (DSS): An AI-powered system that assists administrators in making decisions by providing data-driven insights, predictions, and recommendations.
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Resource Allocation: The process of distributing resources (e.g., funds, staff, materials) efficiently and effectively within the university.
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Predictive Analytics: The use of AI algorithms to analyze historical data and predict future outcomes or trends.
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