The application of artificial intelligence (AI) to cost overrun mitigation in construction projects is explored in this literature review, especially in light of the nature of construction environments, which are very complex and dynamic. There are many underlying reasons for cost overruns, such as project mismanagement, design changes, and site conditions not encountered in the design. In contrast, AI provides unique solutions on the basis of predictive analytics, machine learning, and computer vision in order to facilitate cost estimation accuracy and reduce risks, allocate resources more efficiently, and improve decision-making processes. AI-driven models analyze past data to predict possible budget problems so managers can manage cost related risks in an online or proactive way. AI case studies show cost overrun reduction across projects worldwide. The gaps in the current AI applications and the suggested improvement in its scalability, real-time data integration, and domain-specific knowledge in the AI models for construction cost management are reviewed in this paper. These findings reveal the importance of AI becoming part of the construction landscape to bring cost efficiency and enhance project resilience.