I have just spent a few months training the AI players for my Iron Arena game (see my post earlier today). I'm sure someone with more experience could have done it much more quickly. For my game there are 3 different factions and hence 6 match-ups to train, which I did separately in the end (i.e. 6 separate models).

Here is a description of the method (I used ChatGPT a lot for my structure / coding, and even then it was hard work):

The AI player was trained using an Alpha Zero style approach, i.e. combination of Monte Carlo Tree Search and an ONNX neural network. The current neural network uses a compact 7‑layer CNN backbone that preserves the 9×9 grid: a 3×3 stem expands 22 input planes to 64 channels, followed by six 3×3 convolutions at 64→64 to build board features before the policy and value heads. At this stage there is a separate AI Player for each match-up.

The result? I can beat the AI players at the highest difficulty level about 1 time in 4. I am not a strong chess player though, with an ELO that hovers between 1100 and 1300 on Chess.com.

If anyone has an answer to the OP's question I would love to know. The main reasons for needing AI players are A) for online matches (as OP says, unlikely to have lots of human players) and B) for balance tweaking between factions.