Do you not consider SVD/PCA to be "embeddings"?

Latent Semantic Indexing long precedes word2vec (I believe the initial paper was 1988) but also attempted to derived semantic vectors (and was arguably successful) using SVD on the term-frequency matrix representing a corpus.

I would certainly consider this an example of using "embeddings" that was quite heavily used in practice prior to the explosion of deep learning techniques.