Artificial intelligence promises to revolutionize tire production with predictive quality, real-time monitoring and adaptive control. But how far have we really come? This talk critically examines the gap between expectations and current capabilities. Using examples from laser-based processes, such as innerliner cleaning, sidewall marking and mold cleaning, 4Jet explores where AI delivers tangible benefits and where challenges remain. Issues like data quality and availability, on-premises training and real-time decision-making often limit practical implementation. Are we ready for fully autonomous quality control, or is AI still more hype than reality?

• Where AI already creates value in tire manufacturing, illustrated through laser-based applications such as innerliner cleaning and sidewall marking
• Which technical and organizational barriers limit AI adoption, including data quality, on-premises model training and real-time decision-making
• How close the industry is to autonomous quality control, and what steps are needed to move to reliable, scalable production solutions