There is now considerable interest in comparing functional genomics data across species. One goal of this work is to provide an integrated understanding of genome and phenotype evolution. Most studies of this type have relied on multiple pairwise comparisons of functional genomic data between species, an approach that does not incorporate information about the evolutionary relationships among species. The statistical problems that arise from not considering these relationships can lead pairwise approaches to the wrong conclusions, and are a missed opportunity to learn about biology that can only be understood in an explicit phylogenetic context. Here we examine two recently published studies that compare gene expression across species with pairwise methods. We find problems with both that call their conclusions into question. One study interpreted higher expression correlation between orthologs than paralogs as evidence for the ortholog conjecture, i.e. the hypothesis that gene function evolution is more rapid after duplication than speciation. Instead, we find that this pattern is due to the structure of the gene phylogenies, not different rates of expression evolution, and is the expected pattern when rates are the same following duplication and speciation. The second study interpreted pairwise comparisons of embryonic gene expression across distantly related animals as evidence for a distinct evolutionary process that gave rise to animal phyla. Instead, we find that the pattern they identified is due to unique features of a single species that impact multiple pairwise comparisons that include that species. In each study, distinct patterns of pairwise similarity among species were interpreted as evidence of particular evolutionary processes, but instead reflect the structure of phylogenies. These reanalyses concretely demonstrate the inadequacy of pairwise comparisons for analyzing functional genomic data across species, and indicate that it will be critical to adopt phylogenetic comparative methods in future functional genomics work. Fortunately, phylogenetic comparative biology is also a rapidly advancing field with many methods that can be directly applied to functional genomic data.