In project-based production models, which typically adopt a fixed-position layout, occupational safety is a key challenge due to the unique characteristics and high degree of customization of each project. This approach involves the constant mobilization of equipment, materials, and workers, which increases the risk of accidents and requires precise safety management. The integration of Artificial Intelligence (AI) in this context represents a transformative tool for enhancing safety and optimizing workflow. This study has been conducted using a review of literature and case studies in industrial sectors such as aerospace, construction, and shipbuilding industries. Through this methodology, key AI applications have been identified including real-time monitoring, predictive risk analysis and the automation of compliance evaluation. The results indicate that AI implementation significantly enhances workplace safety by enabling early risk detection, the customization of safety protocols, and the optimization of resource utilization. In the aerospace industry, for example, improvements have been observed in component condition monitoring and fault diagnosis. In construction, AI has facilitated the detection of regulatory non-compliance and accident prevention through real-time monitoring systems. In shipbuilding, the integration of sensors and IoT networks has enabled more efficient control of working conditions and employee safety. These findings suggest that AI not only contributes to reducing the incidence and severity of workplace accidents but also optimizes operational efficiency, ensuring a safer working environment adapted to the challenges of the industry today.