Transformative applications of artificial intelligence in lithium battery materials science: advancements and future prospects

Abstract Artificial intelligence (AI) technologies have transformed the field of materials science by enabling efficient data‐driven approaches for property prediction and material discovery. Here, we provide an in‐depth analysis of AI applications in materials science, focusing on data collection, property prediction, material discovery, and autonomous experimentation. We summarize the primary data sources and increased utility of large language models, which have significantly expedited the material discovery process. Additionally, we examine the application of AI to predict the key properties, emphasizing the transformative role of AI for lithium batteries. Although numerous challenges persist, advancements in AI‐driven tools and methodologies provide avenues for accelerating innovation in materials science.