One remark about AutoML. It seems that when you want to store the resulting workflow and load it again you will have to remove the input and output that has been stored with the workflow so as to allow the use of the new data.
Also then with the Workflow Executor you will have to adjust the input and output sessions once.
Now the Executor is ready to receive the new data (which obviously has to have the same structure as the training data). And will give the results:
Apparently you can do the same with Cal Workflow Services node and get the new data scored.
If you open the workflow you will see that the models and all the other parameters (besides the input and output data) has been stored in encapsulated objects from the capture of the workflow elements in the AutoML node. So the models etc will be there.