Program and Development Research

Program and Development Research

Efficient Government Budgeting Based on Artificial Intelligence in the Future of Iran: Scenarios, Policies, and Actions

Document Type : Original Article

Authors
1 Department of Strategy and Business Policy, Faculty of Business Management, College of Management, University of Tehran, Tehran, Iran.
2 Ph.D. student in Business Administration - Business Policy, University of Tehran, Tehran, Iran.
10.22034/pbr.2024.205536
Abstract
Introduction: Government budgeting is of great significance in assisting countries to achieve the economic and social objectives. With the expansion of modern technologies, especially artificial intelligence, new opportunities have emerged to improve financial and budgetary processes. With its advanced capabilities in data analysis and needs forecasting, AI can help increase accuracy and efficiency in resource allocation. These technologies not only transform existing processes but can also make a significant improvement in transparency and accountability in government financial affairs.
Objective: The objective of this study is twofold: first, to evaluate the efficiency of using artificial intelligence technologies such as neural networks and genetic algorithms in optimizing the allocation of government budgeting resources. Second, to determine the impact of these technologies on the transparency and accountability of budgeting processes to enhance public participation and trust.
Method: The study employs a mixed-method approach. Data analysis is conducted through scenario modeling and and the Multipol software. Additionally, interviews and questionnaires with experts in related fields have been organized to provide our audience with a better understanding of the existing challenges and opportunities.
Result: Findings indicate that the use of artificial intelligence can significantly increase accuracy, transparency, and efficiency in government budgeting. Artificial intelligence enables policymakers to adjust resource allocation based on more accurate data and optimized forecasts.
Keywords

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