Somatic embryogenesis (SE), a manifestation of plant cellular totipotency, holds significant application value in plant germplasm resource conservation, elite tree breeding and industrial utilization, cultivar and gene-editing applications. However, substantial variations in embryogenic capacity exist among tree species, coupled with the absence of universally applicable protocols, highlighting an urgent need to improve dedifferentiation efficiency and somatic embryo induction rates. Elucidating the molecular mechanisms underlying somatic embryogenesis is essential for further enhancing embryogenesis efficiency, optimizing somatic embryo induction systems, and expanding industrial production. Single-cell sequencing (scRNA-seq) has emerged as a transformative tool for dissecting transcriptional heterogeneity, epigenetic dynamics, and cell fate transitions at single-cell resolution, offering novel insights into the regulatory networks underlying SE. However, the application of scRNA-seq in woody species is constrained by lignified cell walls, vascular complexity, and limited species-specific databases. This review systematically outlines the technological evolution of scRNA-seq, strategies for preparing woody plant tissues (e.g., protoplast isolation, nuclei extraction), and bioinformatic workflows for data analysis. By integrating case studies in Dimocarpus longan and Cocos nucifera, we highlight the utility of scRNA-seq in reconstructing developmental trajectories, unraveling hormone signaling crosstalk, and enabling multi-omics integration during SE. For instance, in D. longan, scRNA-seq revealed 12 cell clusters in embryogenic callus, with pseudotime analysis identifying histone deacetylation as a key regulator of early embryogenesis. Similarly, coconut studies demonstrated distinct transcriptional landscapes among zygotic embryos, callus, and somatic embryos, pinpointing CnGRF12 as a critical transcription factor in cell fate determination. Challenges in woody plant scRNA-seq include spatial information loss during cell dissociation, technical noise from protoplast preparation, and the scarcity of cross-species marker gene databases. To address these, we propose strategies such as combining snRNA-seq with spatial transcriptomics, optimizing enzymatic digestion protocols, and establishing unified annotation frameworks. Furthermore, advancements in multi-omics platforms (e.g., scATAC-seq, CITE-seq) and computational tools (e.g., Monocle for trajectory inference) are discussed as avenues to enhance resolution and biological relevance. Future directions emphasize the need for large-scale single-cell atlases, standardized protocols for recalcitrant species, and collaborative databases to bridge knowledge gaps between model and non-model plants. By leveraging these advancements, scRNA-seq holds immense potential to accelerate mechanistic studies of SE, optimize regeneration systems, and advance precision breeding in forestry.