Open Educational Resources (OERs) have faced multiple persistent challenges affecting their quality and efficacy. These challenges have been well documented by Porcello & Hsi (2013), described as “converging towards common metadata”, “balancing expert and community definitions of quality”, “community input”, and “interoperability”. Although some of these challenges have been tackled in individual instances, the struggles of the field, in general, still remain. In this perspective paper, we point to new innovations and applications of generative AI in education to address these long-standing challenges. Additionally, we examine how different applications of LLMs provide new insights into how communities can leverage this technology to interact with and adapt OERs. We argue that framing generative AI tools themselves as the next generation of OERs can be a productive lens with which to approach LLM research in education.