ABSTRACT
This study determines the significant relationship between the extent of judicious utilization of artificial intelligence (AI) tools in performing administrative tasks and data-driven decision-making among school heads and teachers. This study employs a descriptive-correlational research design to evaluates the extent of judicious utilization of artificial intelligence (AI) tools in performing administrative tasks and data-driven decision-making among school heads and teachers This was conducted in Hibunawan ES, Igang ES, Maganhan ES, Kansungka ES, Gacat ES, San Isidro ES, Can-ipa ES, Baybay I CS of Baybay I District Baybay, City Division. The forty-five (45) teachers and school heads assigned in the identified schools were included in the study. This study utilized survey questionnaire that will measure the extent of judicious utilization of artificial intelligence (AI) tools in performing routinary administrative tasks of school heads, perceived level of administrative efficiency resulting from the use of AI tools and extent of utilizing AI tools to support evidence-based decision-making in administrative practices. The survey was taken from the study of Sova et al., 2024 about “Artificial intelligence tool adoption in higher education”. The study revealed a significant relationship between the extent of utilizing artificial intelligence (AI) tools in performing routinary administrative tasks of school heads and perceived level of administrative efficiency resulting from the use of AI tools. Further, in this study, a significant relationship also exists between the extent of utilizing artificial intelligence (AI) tools in performing routinary administrative tasks of school heads and extent of utilizing AI tools to support evidence-based decision-making in administrative practices. Based on the findings, it can be concluded that school heads and teachers generally manifested a favorable perception toward the judicious use of Artificial Intelligence (AI) tools in educational administration. Respondents agreed that AI tools contribute positively to administrative automation, data management, reporting, communication, productivity, and evidence-based decision-making. Moreover, the findings showed that AI tools significantly support evidence-based decision-making practices. Respondents agreed that AI applications strengthen data analysis, planning, forecasting, policy development, and real-time decision support. This implies that AI technologies enable educational leaders to make more informed, reliable, and data-driven decisions that contribute to institutional improvement and effective governance. Therefore, the study concludes that the responsible integration of AI technologies plays a vital role in enhancing educational administration and institutional performance.
Keywords: Judicious Use, Artificial Intelligence Tools, Leveraging Administrative Efficiency, Data-Driven Decision-Making
INTRODUCTION
In the rapidly evolving digital era, organizations across sectors are increasingly integrating advanced technologies to improve operational efficiency and enhance decision-making processes. Among these technologies, Artificial Intelligence (AI) has emerged as a transformative tool capable of analyzing large datasets, automating repetitive tasks, and providing predictive insights that support evidence-based decision making. AI systems can process complex information at speeds far beyond human capabilities, allowing organizations to generate insights that guide strategic planning and resource allocation. Consequently, the adoption of AI tools has become a significant driver of organizational efficiency and innovation in both private and public institutions.
Artificial Intelligence is widely recognized for its capacity to streamline administrative processes (Fonseca, 2025). Through automation and intelligent data processing, AI can reduce the time required for routine administrative tasks such as data management, report generation, scheduling, and document processing. Studies indicate that AI-driven administrative technologies can significantly improve productivity by minimizing manual intervention and enabling organizations to focus on higher-level strategic activities. In addition, AI technologies facilitate improved organizational workflows and decision accuracy by transforming raw data into actionable insights. These capabilities allow institutions to optimize operations and make more informed decisions based on reliable data analytics.
In the context of decision-making, AI has demonstrated substantial potential to enhance efficiency and accuracy. AI-enabled systems can analyze vast amounts of structured and unstructured data, detect patterns, and provide predictive recommendations that assist leaders in making strategic decisions. Research has shown that organizations adopting AI technologies experience improved decision-making efficiency and overall organizational performance. By reducing human bias and providing data-supported recommendations, AI can help leaders make more rational and objective decisions (Song et al., 2025).
Recent empirical studies further highlight the transformative role of AI in organizational management. For instance, a study involving multiple organizations found that AI adoption significantly improved decision-making efficiency by accelerating the speed of analysis and enhancing forecast accuracy. The study reported that organizations using AI technologies experienced faster decision-making processes and improved resource utilization, demonstrating the strategic value of AI-driven management systems (Zhu, 2025).
Within educational and institutional leadership, AI is increasingly viewed as a powerful tool for supporting data-driven decision making. School leaders and administrators are often required to manage large volumes of information related to student performance, resource allocation, and institutional planning. AI technologies can assist administrators in analyzing educational data, identifying trends, and making evidence-based decisions that improve institutional effectiveness. Studies on educational leadership suggest that AI has the potential to enhance leadership practices by providing analytical support that strengthens policy implementation and organizational planning.
Despite these promising developments, the integration of AI into administrative and leadership practices remains an emerging area that requires further investigation. While AI tools offer numerous benefits, challenges such as data privacy concerns, ethical considerations, and the need for technological readiness continue to influence their adoption and effective utilization. Researchers emphasize that successful AI implementation requires organizational support, proper training, and clear governance frameworks to ensure that AI systems complement human judgment rather than replace it.
Given the growing reliance on technology in organizational management, it is essential to examine how AI tools can be effectively leveraged to enhance administrative efficiency and support data-driven decision making. Understanding the role of AI in improving administrative processes can help institutions identify strategies for optimizing their operations and strengthening leadership practices. Moreover, investigating the integration of AI tools in administrative contexts can provide valuable insights into how organizations can harness digital innovations to achieve more efficient, transparent, and evidence-based management systems.
Therefore, this study aims to explore how Artificial Intelligence tools can be utilized to improve administrative efficiency and facilitate data-driven decision making. The findings of this study may contribute to the development of innovative administrative practices and provide guidance for leaders seeking to integrate AI technologies into their organizational decision-making processes.
This study determines the significant relationship between the extent of judicious utilization of artificial intelligence (AI) tools in performing administrative tasks and data-driven decision-making among school heads and teachers in selected schools of Baybay 1 District, Baybay City Division. The findings of the study were basis for the proposed instructional supervision plan.
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