Tire Repairers and Changers

Repair and replace tires.

The occupation "Tire Repairers and Changers" has an automation risk of 24.7%, which is slightly below the base risk of 25.0%. This indicates that while certain aspects of the job are susceptible to automation, a significant portion of the work still requires human involvement. The moderate risk level arises from both the mix of routinely repetitive tasks and hands-on problem solving that defines this role. Many operations performed by tire repairers are mechanical and could, in theory, be streamlined or even replaced by advanced robotics or specialized tire-changing machines. However, the nature of repairs, diverse environments, and the need for flexible adaptation to unexpected scenarios help preserve some job security for workers in this field. Among the tasks most likely to be automated are raising vehicles with hydraulic jacks, remounting wheels onto vehicles, and unbolting and removing wheels using hand or power tools. These tasks are primarily mechanical, repetitive, and require precise but predictable movements, making them ideal candidates for robotics and automatic tire service equipment. Several automated systems already exist for lifting vehicles and removing wheels in commercial garages, which further underscores the susceptibility of these tasks to automation. As technology and artificial intelligence advance, the speed and efficiency with which these tools operate can be expected to further reduce the need for manual labor, especially in high-throughput service centers. On the other hand, some tasks are much more automation-resistant due to their complexity or context dependence. For example, driving service trucks to industrial sites or responding to emergency calls requires situational judgment, navigation skills, and the ability to adapt quickly—capabilities that current automation technologies struggle with, especially outside controlled environments. Patching tubes with adhesive or sealing rubber patches using vulcanizing plates, and applying rubber cement to buffed casings before vulcanization, demand a level of manual dexterity and nuanced problem-solving that machines currently cannot consistently replicate. The main bottleneck skills identified are related to originality, though their levels are relatively low (2.1% and 2.0%). This suggests that while creativity is not a predominant requirement, the occasional need for innovative or non-standard solutions further shields some aspects of this occupation from full automation.