Artificial Intelligence (AI) is  public policy by enabling data-driven governance and enhancing the efficiency, transparency, and responsiveness of governmental decisionmaking. With the exponential growth of public data, AI technologies such as machine learning, natural language processing, and predictive modeling are being deployed to assist in policy design, implementation, and evaluation. These tools allow policymakers to anticipate outcomes, identify risks, allocate resources efficiently, and detect social patterns at scale. This paper explores the foundational technologies behind AI in public policy, with a particular focus on predictive analytics and decision-support systems. It discusses core use cases including policy forecasting, fraud detection, and crisis response. Case studies from global governments and institutions highlight the transformative impact of AI in managing public health, education, transportation, and environmental policy. Ethical and regulatory considerations such as algorithmic bias, data privacy, and accountability are critically examined. The paper also discusses the challenges of data integration, policy interpretability, and stakeholder trust. Future innovations such as explainable AI, participatory algorithms, and real-time policy simulation are anticipated to redefine the future of governance. AI offers immense potential to make public policy more evidencebased, equitable, and agile in addressing complex societal challenges. Keywords: AI, Modelling, Ethical, Governance