The accelerated development of railway systems is based on modernization of infrastructure, interoperability of signaling and telecommunication systems, and digital transformation of operational processes. Modern railway traffic management requires efficient coordination between infrastructure systems, dispatch centers, rolling stock, and information technologies. Due to the complexity of railway operations, human errors may occur during traffic regulation and transport management. This paper presents an electronic business model for railway traffic and transport regulation based on artificial intelligence and advanced information and communication technologies. The proposed model integrates internal databases, intelligent algorithms, and digital communication systems into a unified platform for sustainable and safe railway traffic management. Particular attention is focused on the application of AI systems in decision-making processes, predictive analytics, automation, and operational safety. The paper also analyzes the advantages and limitations of AI implementation in railway systems and discusses future development trends in digital railway transport. Research results indicate that AI-based electronic business models can significantly improve operational efficiency, interoperability, safety, and sustainability in railway traffic regulation.