Initial classification of acute leukemia involves the assignment of blasts to cell states within the hematopoietic hierarchy based on morphological and immunophenotypic features. Yet, these traditional classification approaches lack precision, especially at the level of immature blasts. Single-cell RNA-sequencing (scRNA-seq) enables precise determination of cell state using thousands of markers, thus providing an opportunity to re-examine present-day classification schemes of acute leukemia. Here, we developed a detailed reference map of human bone marrow hematopoiesis from 263,519 single-cell transcriptomes spanning 55 cellular states. Cell state annotations were benchmarked against purified cell populations, and in-depth characterization of gene expression programs underlying hematopoietic differentiation was undertaken. Projection of single-cell transcriptomes from 175 samples spanning acute myeloid leukemia (AML), mixed phenotype acute leukemia (MPAL), and acute erythroid leukemia (AEL) revealed 11 subtypes involving distinct stages of hematopoietic differentiation. These included AML subtypes with notable lymphoid or erythroid lineage priming, challenging traditional diagnostic boundaries between AML, MPAL, and AEL. Quantification of lineage priming in bulk patient cohorts revealed specific genetic alterations associated with this unconventional lineage priming. Integration of transcriptional and genetic information at the single-cell level revealed how genetic subclones can induce lineage restriction, differentiation blocks, or expansion of mature myeloid cells. Furthermore, we demonstrate that distinct cellular hierarchies can co-exist within individual patients, providing insight into AML evolution in response to varying selection pressures. Together, precise mapping of hematopoietic cell states can serve as a foundation for refining disease classification in acute leukemia and understanding response or resistance to emerging therapies.