The packaging of DNA into chromatin determines the transcriptional potential of cells and is central to eukaryotic gene regulation. Case sequencing studies have revealed mutations to proteins that regulate chromatin state, known as chromatin remodeling factors, with causal roles in neurodevelopmental disorders. Chromodomain helicase DNA binding protein 8 (CHD8) encodes a chromatin remodeling factor with among the highest de novo loss-of-function mutation rates in patients with autism spectrum disorder (ASD). However, mechanisms associated with CHD8 pathology have yet to be elucidated. We analyzed published transcriptomic data across CHD8 in vitro and in vivo knockdown and knockout models and CHD8 binding across published ChIP-seq datasets to identify convergent mechanisms of gene regulation by CHD8. Differentially expressed genes (DEGs) across models varied, but overlap was observed between downregulated genes involved in neuronal development and function, cell cycle, chromatin dynamics, and RNA processing, and between upregulated genes involved in metabolism and immune response. Considering the variability in transcriptional changes and the cells and tissues represented across ChIP-seq analysis, we found a surprisingly consistent set of high-affinity CHD8 genomic interactions. CHD8 was enriched near promoters of genes involved in basic cell functions and gene regulation. Overlap between high-affinity CHD8 targets and DEGs shows that reduced dosage of CHD8 directly relates to decreased expression of cell cycle, chromatin organization, and RNA processing genes, but only in a subset of studies. This meta-analysis verifies CHD8 as a master regulator of gene expression and reveals a consistent set of high-affinity CHD8 targets across human, mouse, and rat in vivo and in vitro studies. These conserved regulatory targets include many genes that are also implicated in ASD. Our findings suggest a model where perturbation to dosage-sensitive CHD8 genomic interactions with a highly-conserved set of regulatory targets leads to model-specific downstream transcriptional impacts.