<p>The transition to electromobility is a key step in the transformation of the transportation sector. By reducing dependence on fossil fuels and increasing the use of renewable energy sources, this shift is critical to achieving global climate goals. As policies around the world encourage the adoption of electric vehicles, the growing number of these vehicles is accompanied by a sharp increase in used battery systems. The worldwide number of end-of-life battery systems is expected to grow exponentially. The potential applications for these batteries are numerous and depend on their condition. Electric vehicle batteries can be reused for second-life applications or recycled into valuable raw materials. However, the disassembly process, which is crucial for both reuse and efficient recycling, is currently performed manually and is labor-intensive. This is due to the wide variety of battery models and manufacturers, making the process cost-efficient and difficult to scale. The integration of automation, particularly through the use of artificial intelligence (AI), presents a promising solution to these challenges. AI has the potential to tackle several issues related to electric vehicle battery recycling, including the variability of battery models, the unpredictability of post-use conditions, and the need for scalable disassembly processes. By automating the disassembly of electric vehicle batteries, AI could enhance the efficiency and sustainability of the recycling process. This paper offers a comprehensive overview of existing AI algorithms and explores their potential for automating the disassembly of electric vehicle batteries.</p>