Large galaxy surveys have dramatically improved our understanding of astrophysics and cosmology in the high-redshift universe, but they are fundamentally limited by the need to integrate long enough to detect each individual source. Line intensity mapping has recently arisen as a powerful alternative to these surveys, offering access to fainter sources and larger volumes than conventional techniques. There has been a surge of experimental interest in this technique, with surveys planned or in progress across the electromagnetic spectrum. In this talk, I will describe the wide variety of science which we will obtain from these experiments in the next few years and illustrate the methods by which we can go from maps of confused line emission to useful astrophysics. I will show how intensity maps can give new insights into topics ranging from star formation to the high-redshift ISM to the Hubble constant tension. I will further discuss the utility of combining intensity maps with conventional surveys, both for systematics control and for studying processes like AGN feedback. I will close with a discussion of how modern machine learning methods can be used to further extend what we can learn from these surveys.