Minister of Transportation and Infrastructure Uraloğlu stated that artificial intelligence can detect potential failures in automatic train inspection stations before they happen. Minister of Transportation and Infrastructure Abdulkadir Uraloğlu emphasized that the Artificial Train Inspection Station (ATIS) System has been integrated with artificial intelligence technology, stating that “AI algorithms in automatic train inspection stations analyze vast amounts of data to predict failures before they occur, sending early warnings to maintenance teams for preventative interventions.” In a written statement, Uraloğlu highlighted that the Republic of Turkey State Railways (TCDD) General Directorate has undergone a significant transformation in railway transportation through investments in digitization and AI-based technologies. Uraloğlu further explained that they have accelerated the integration of artificial intelligence with local and national solutions to modernize Turkey’s railway network in accordance with the digital age. Developed in collaboration between TCDD and TÜBİTAK, the ATIS System has been successfully integrated with artificial intelligence, allowing for the real-time analysis of all critical components of moving trains using AI-based image processing and sensor systems to produce instant data. With this technology, wheel wear, flaws in brake discs, axle bearing temperatures, load imbalances, and other mechanical components are analyzed in real-time, enabling the prevention of unexpected failures, reduction in maintenance costs, and maximization of train operation continuity. Additionally, remote monitoring and analysis across railway lines in Turkey are improving maintenance processes significantly. Uraloğlu noted the widespread use of “predictive” maintenance systems to ensure the continuous monitoring of railway infrastructure and more efficient management of maintenance processes, as specially equipped railway vehicles intervene before failures occur, increasing operational continuity and reducing costs. Stressing that safety is a top priority in railway transportation, Uraloğlu highlighted how AI-based analysis systems can detect distractions in train drivers by monitoring their facial expressions, eye closure times, and head positions, issuing warnings when necessary. Uraloğlu underlined how the Eryaman Monitoring Center constantly monitors high-speed train (YHT) lines, using smart cameras and sensors to oversee critical infrastructure such as tunnels, bridges, culverts, and viaducts around the clock. Any anomalies detected remotely prompt rapid notifications to the relevant teams, minimizing response times. The condition of railway infrastructure including bridges, culverts, and tunnels are continuously analyzed to optimize maintenance processes via early warning systems. Finally, Uraloğlu predicted the wider adoption of autonomous trains and AI-based signalization systems in the coming years, anticipating that AI-supported energy management systems will facilitate maximum efficiency with minimal energy consumption for trains. These advancements will not only reduce carbon emissions but also decrease operational costs. Intelligent assistants and chatbots will analyze passenger needs to offer the most suitable travel plans, enhancing passenger comfort and taking it to a whole new level with digitization.