Enhancing Financial Reporting in Academic Institutions by Adopting AI tools: University of Nizwa is a case study

Financial reporting processes in academic institutions are one of the main sectors that must be developed by adopting Artificial Intelligence (AI) tools and applications. The study focuses on adopting artificial intelligence tools in financial reporting, as one of the facilities provided to improve the process of financial reporting at the University of Nizwa, Oman, as one of the academic situations dealing with AI transformation. The outcome of reporting in the financial sectors almost plays a crucial role in ensuring transparency, accountability, and compliance with International Financial Reporting Standards (IFRS); however, traditional methods often suffer from inefficiencies, human errors, and delays. By automating repetitive tasks, enhancing data accuracy, and enabling real-time analytics, AI offers promising solutions to these challenges. Employing a mixed-methods approach, the study combines quantitative and qualitative data through structured questionnaires distributed to financial professionals at the University of Nizwa and secondary data analysis from literature and documents. The findings reveal that AI significantly enhances financial reporting accuracy (80% agreement), timeliness (75% improvement in report generation), and compliance with IFRS (65%). Statistical analysis, including chi-square tests, confirms a strong correlation between AI adoption and these improvements. However, key challenges such as high implementation costs (78%), limited technical expertise (65%), and resistance to change hinder adoption. Regression analysis highlights that management support (β = 0.65) and IT infrastructure (β = 0.52) are critical success factors for AI integration. According to the study findings, the most recommendation in providing training and activities, supporting in strengthening IT and adopting AI with securing management support. A phased implementation strategy is suggested to mitigate cost concerns and ease the transition process. The one challenge is the missing of create a strategic plan in impact the financial reporting for getting success vision and mission.

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Publication Details

Journal
East Journal of Human Science
Published
2025-09-12
DOI
https://doi.org/10.63496/ejhs.vol1.iss5.146
Primary Topic
Stock Market Forecasting Methods
Type
article
Field-Weighted Citation Impact
0.00
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article

Enhancing Financial Reporting in Academic Institutions by Adopting AI tools: University of Nizwa is a case study

Dr Said Mohammed ALRASHDI, Saif Ahmed Alharthy
East Journal of Human Science
Stock Market Forecasting Methods
article

Enhancing Financial Reporting in Academic Institutions by Adopting AI tools: University of Nizwa is a case study

Dr Said Mohammed ALRASHDI, Saif Ahmed Alharthy
article en

Abstract

Financial reporting processes in academic institutions are one of the main sectors that must be developed by adopting Artificial Intelligence (AI) tools and applications. The study focuses on adopting artificial intelligence tools in financial reporting, as one of the facilities provided to improve the process of financial reporting at the University of Nizwa, Oman, as one of the academic situations dealing with AI transformation. The outcome of reporting in the financial sectors almost plays a crucial role in ensuring transparency, accountability, and compliance with International Financial Reporting Standards (IFRS); however, traditional methods often suffer from inefficiencies, human errors, and delays. By automating repetitive tasks, enhancing data accuracy, and enabling real-time analytics, AI offers promising solutions to these challenges. Employing a mixed-methods approach, the study combines quantitative and qualitative data through structured questionnaires distributed to financial professionals at the University of Nizwa and secondary data analysis from literature and documents. The findings reveal that AI significantly enhances financial reporting accuracy (80% agreement), timeliness (75% improvement in report generation), and compliance with IFRS (65%). Statistical analysis, including chi-square tests, confirms a strong correlation between AI adoption and these improvements. However, key challenges such as high implementation costs (78%), limited technical expertise (65%), and resistance to change hinder adoption. Regression analysis highlights that management support (β = 0.65) and IT infrastructure (β = 0.52) are critical success factors for AI integration. According to the study findings, the most recommendation in providing training and activities, supporting in strengthening IT and adopting AI with securing management support. A phased implementation strategy is suggested to mitigate cost concerns and ease the transition process. The one challenge is the missing of create a strategic plan in impact the financial reporting for getting success vision and mission.

East Journal of Human ScienceVol. 1(5)
University of Nizwa (OM)
Openalex Percentile: Top 71%
Stock Market Forecasting Methods
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