The construction industry faces persistent challenges related to safety and risk management due to its dynamic, high-risk, and resource-intensive nature. Traditional risk mitigation approaches, while effective to an extent, are limited in adaptability, scalability, and real-time responsiveness. With recent advancements in digital technologies, artificial intelligence (AI) has emerged as a transformative solution capable of enhancing risk identification, accident prediction, and safety monitoring in construction projects. This review critically examines existing literature on conventional risk management methods and explores how AI techniques such as machine learning, natural language processing, computer vision, and Internet of Things (IoT)-based systems are being leveraged for improved safety outcomes. It further highlights the advantages of AI integration, implementation challenges, organizational barriers, and ethical concerns. The paper also discusses the future of AI-enabled safety systems, including integration with Building Information Modeling (BIM) and digital twins, and identifies key research gaps for future exploration. Overall, AI has the potential to shift construction safety management from a reactive to a predictive and preventive paradigm, contributing to safer and more efficient project delivery.