<p>Battery technologies are essential for modern energy infrastructure, and the materials they comprise play a critical role in determining their performance and cost. Traditionally, the discovery and optimization of battery materials have been largely driven by human intuition and manual experimentation. The integration of high-throughput computation, and more recently, artificial intelligence and automation, is opening new possibilities for more rapid and efficient development of next-generation battery materials. In this short review, we highlight recent advancements in applying artificial intelligence and automation to the study of electrode materials, liquid electrolytes, and solid electrolytes. We also discuss the key challenges and emerging solutions to further advance this rapidly evolving field.</p> Graphical abstract <p></p>