Effects of Artificial Intelligence on the Accuracy and Efficiency of Budget Forecasting of the Ministry of Finance of Ethiopia

Abstract

Accurate and efficient budget forecasting is essential for effective public financial management and evidence based decision making. This study examined the effects of Artificial Intelligence on the accuracy and efficiency of budget forecasting of the Ministry of Finance of Ethiopia. A mixed research design was employed. The data was collected from 181 employees using a structured questionnaire and 15 respondents via semi structured interviews and open-ended responses. The data was analyzed using descriptive statistics and regression analysis. The findings revealed that Artificial Intelligence significantly improves forecasting efficiency by reducing forecasting time, enabling rapid analysis of budget scenarios and supporting improved decision making. However, Artificial Intelligence had a limited effect on forecasting accuracy compared to its strong impact on efficiency. Although some improvements in accuracy were observed, challenges such as poor data quality, limited technical skills, inadequate training and low confidence in Artificial Intelligence outputs continue to affect forecasting performance. The qualitative findings supported the quantitative results indicating that employees recognize Artificial Intelligence as useful for improving efficiency but believe that further improvements are required before substantial gains in forecasting accuracy can be achieved. The study implied that Artificial Intelligence has strong potential to improve budget forecasting of the Ministry of Finance of Ethiopia by enhancing efficiency and supporting evidence based decision making. However, achieving significant improvements in forecasting accuracy requires cleaner data, continuous staff training, improved technological infrastructure and stronger leadership support for Artificial Intelligence adoption