Biodiversity inventory in Kenya has been ongoing for just about a century and a half, coinciding with the arrival of naturalists from Europe and elsewhere in Africa. Since the first collections in the mid-to-late 1800s, there has been a steady increase of plant surveys, frequency of inventory and discovery of new species that have considerably increased knowledge of faunal and floristic elements. However, as in all other countries, biological collection activities are more often than not, ad hoc, resulting in gaps in knowledge of species and their habitats. While Kenya is relatively rich, with a succulent flora of about 428 taxa, it is apparent that the list is understated owing to, among other factors, difficulty of preparing herbarium material and restricted access to occurrence sites. This study investigated completeness of geographic knowledge of succulent plants in Kenya with the aim of establishing species distribution patterns and identifying gaps that will guide and justify priority setting for future work on the group. Species data were filtered from the general BRAHMS database at the East African Herbarium and extracted as a Microsoft Excel file for further processing. To get an immediate visual impression of typical diversity of species and collection patterns across the country, preliminary analysis was performed using the MS Excel and ArcGIS software. Subsequently, data were cleaned via an iterative series of inspections and visualizations designed to detect and document inconsistencies in taxonomic concepts, geographic coordinates and dates of collection. Eight grid squares fulfilled criteria for completeness of inventory: one centred on the city of Mombasa, one centred on the Kulal-Nyiro complex, one centred on Garissa, one centred on Baringo and four grid squares centred on the Nairobi–Nakuru–Laikipia complex. The little known areas, mostly in the west, north and north-eastern regions of the country were found to be extremely isolated from well-known sites, both geographically and ecologically. These localities should be prioritised for future inventory as they are likely to yield species new to science, to the flora, or contribute new knowledge on habitats. To avoid inconsistencies and data leakage, inventory and documentation needs streamlining to generate standardised data that should be digitised to enhance access and synthesis.