This is not the case, according to the current explanation in the iNat help:
Which taxa are included in the computer vision suggestions?
This has changed over time and may change before this FAQ is updated again, as we are continually working on improving the training process. But basically, here’s what’s needed for a species to be included in the Computer Vision model:
There must be a [sic] least 100 photos of the species and 60 observations of the species, and we don’t choose more than 5 photos from an observation to train the model. Observations do not need to be Research Grade in order to be used in training, but observations with a matching Community ID will be prioritized.
Some photos that are not included in the training phase are used to test and validate the model. These must have a Community ID.
Because of this, not every species with at least 100 photos and 60 observations will meet the requirements to be included in a training run. It’s dependent on how many photos there are per observation, and whether the randomly chosen group of observations meets the requirements.
If no species within a broader taxon like genus or family meets the requirements, we may train the model on that genus or family, based on those photos.
(emphasis in original)