The construction industry, particularly in housing projects, faces numerous challenges, including ensuring regulatory compliance, maintaining high-quality standards, and managing risks such as delays, cost overruns, and safety concerns. This paper explores the integration of Artificial Intelligence (AI) into construction to address these issues through a smart, AI-driven framework for compliance, quality assurance, and risk management. By reviewing existing literature on AI applications in construction, the paper highlights how AI technologies, such as predictive analytics, natural language processing, and machine learning, can significantly improve construction outcomes by streamlining compliance processes, enhancing quality control, and mitigating risks in real-time. The paper also discusses the key design principles for creating an AI framework tailored to construction, examining how AI can monitor regulatory adherence, ensure quality standards, and predict potential project risks. While AI presents vast opportunities, the paper identifies challenges such as technological integration, financial constraints, and regulatory hurdles that may hinder its widespread adoption. Proposed solutions, including AI-based decision-support tools and cloud-based platforms, aim to overcome these challenges. Finally, the paper emphasizes the need for future research, particularly in areas like the integration of AI with Building Information Modeling (BIM), the development of universal standards for AI in construction, and the validation of AI frameworks through case studies. This research provides valuable insights into the potential of AI to transform the construction industry, offering recommendations for further development and implementation in housing projects.