Minister of Transportation and Infrastructure Uraloğlu stated that artificial intelligence can detect potential failures in automatic train inspection stations in advance. Minister of Transportation and Infrastructure Abdulkadir Uraloğlu indicated that the Automatic Train Inspection Station (OTMİ) System has been integrated with artificial intelligence, saying that “artificial intelligence algorithms in automatic train inspection stations evaluate large amounts of collected data to detect potential failures before they occur and send early warnings to maintenance teams for preventive interventions.” He highlighted that TCDD has brought about a significant transformation in railway transportation through investments in digitization and AI-based technologies. Uraloğlu emphasized that they have accelerated the integration of artificial intelligence with local solutions to modernize Turkey’s railway network. He mentioned that the OTMİ System developed through TCDD-TÜBİTAK collaboration has been integrated with artificial intelligence. Uraloğlu pointed out that the system enables the analysis of all critical components of moving trains, generating real-time data by scanning each part in detail. With this technology, Uraloğlu emphasized that wheel wear, faults in brake discs, axle bearing temperatures, load imbalances, and other mechanical components are analyzed in real-time. He stated, “Artificial intelligence algorithms in automatic train inspection stations evaluate large amounts of collected data to detect potential failures before they occur and send early warnings to maintenance teams for preventive interventions. This prevents unexpected failures, reduces maintenance costs, and maximizes train service continuity. Additionally, by providing remote monitoring and analysis capabilities across Turkey’s railway lines, we are significantly improving maintenance processes.” Minister Uraloğlu mentioned that “predictive” maintenance systems have been widely implemented to continuously monitor railway infrastructure and efficiently manage maintenance processes. Equipped with special sensors, railway vehicles enable intervention before malfunctions occur, thereby increasing operational continuity and significantly reducing costs. Uraloğlu highlighted that safety is a top priority in railway transportation, mentioning that AI-based analysis systems track the facial expressions, closing times of eyelids, and head positions of train drivers to detect distraction and issue warnings when necessary. Uraloğlu emphasized that the Eryaman Monitoring Center continuously monitors high-speed train (YHT) lines, utilizing smart cameras and sensors to monitor critical infrastructure such as tunnels, bridges, culverts, and viaducts 24/7. Moreover, when any issues on the lines are identified through remote monitoring technology, relevant teams are rapidly informed, minimizing intervention time. The condition of structures in railway infrastructure and superstructure, such as bridges, culverts, and tunnels, is continuously analyzed, optimizing maintenance processes through early warning systems. Uraloğlu predicted that autonomous trains and AI-based signaling systems will become more widespread in the coming years. He mentioned that through AI-supported energy management systems, trains will achieve maximum efficiency with minimal energy consumption. This will not only reduce carbon emissions but also lower operating costs. Smart assistants and chatbots will analyze passengers’ needs to provide the most suitable travel plans. Passenger comfort will be greatly enhanced through digitization.