As the higher education sector grapples with the "new normal" of the post-pandemic, the structural issues of the recent past not only remain problematic but have been exacerbated by COVID-related disruptions throughout the education pipeline. Navigating the complexity of higher education has always been challenging for students, particularly at underresourced institutions that lack the advising capacity to provide guidance and support. Areas such as transfer and financial aid are notorious black boxes of complexity, where students lacking financial resources and "college knowledge" are too often left on their own to make decisions that may prove costly and damaging down the line. The educational disruptions that many students have faced during the pandemic will likely deepen this complexity by producing greater variations in individual students' levels of preparation and academic histories, even as stressed institutions have less resources to provide advising and other critical student services. Taken together, these challenges will make it all the more difficult to address the equity gaps that the sector must collectively solve. While not a panacea, recent advances in artificial intelligence methodologies such as machine learning can help to alleviate some of the complexity that students and higher education institutions face.