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"I have a question and I hope someone can assist me.
I have a dataset in which I compare two groups, A and B, using a multigroup analysis.
So far, the results have been promising.

However, I also want to evaluate differences in age within each group.
To achieve this, I divided the original dataset into two age-based datasets (+/- 40 years) and conducted a multigroup analysis for the two groups (A and B) in both age-based datasets.

My question is, is this method appropriate? Should I consider the Bonferroni correction in some manner?

In general, if you have a continuous variable using a split (e.g., median split, or any other arbitrary split) is less reliable than using the original continuous variable as a moderator in the model.
In your particular case, you may also end up with quite small groups that have low power to detect differences. Thus, I would always advice to include age as a moderator to investigate the impact of age differences on relationships.

Thank you very much for your response
My sample size is >4000 customers, so it should be adequate in terms of splitting.

Is this a valid way to handle this research issue`?
I split the dataset into 2 parts based on age (>40 vs <40). Then, I conducted MGA on group A and group B separately, based on each of these age-split datasets. This resulted in a significant finding in group A, on age (< 40 years), on construct Y.

Is it appropiate to report this result, or do i need to include a age moderator in the model?
I am not sure how to include moderator in a MGA analysis...