The thesis examines how AI technologies are transforming public finance, particularly in areas like tax administration, budgeting, fraud detection, and risk management. It highlights how AI can bring efficiency, transparency, and improved decision-making to government financial operations by automating tasks and analyzing large datasets. The study focuses on specific applications, such as AI-powered virtual assistants that help taxpayers navigate complex tax regulations, machine learning algorithms that detect fraud, and AI tools that optimize government spending and budgeting processes. Ethical considerations, including privacy concerns, algorithmic biases, and data security, are also discussed. These challenges must be addressed for AI to be effectively integrated into public finance systems. The thesis suggests that while AI can improve efficiency and reduce costs, it must be implemented thoughtfully, considering potential biases and ethical risks. It concludes with a forward-looking discussion on the future of AI in public finance, emphasizing the need for sound governance, transparency, and ethical frameworks to maximize the benefits of AI while minimizing risks.