Managing data drift when using w2vec embeddings on VertexAI

Question

So I am looking into moving my models from GCP's AI Platform to Vertex AI, my main motivation for it being the fact that Vertex AI has automatic email notifications when your data skews or drifts (https://cloud.google.com/vertex-ai/docs/model-monitoring/using-model-monitoring).

So if you start receiving dodgy data that doesn't resemble the training set, they send you an email telling you which features (columns) of the data you are trying to predict are drifting away from your training data.

However, I am unsure how this would work in my case since my data is text data that has been encoded using word2vec embeddings. Therefore, my dataset has 300 columns but I don't know what feature each of the columns refers to.

Is this sort of data drift analysis still useful in my particular case?

Thank you