Supplementing artificial intelligence (ai) / machine learning (ml) models via action center, ai/ml model retraining hardware control, and ai/ml model settings management

A system, comprising:

• a server comprising one or more artificial intelligence (AI)/machine learning (ML) models or with access to the one or more AI/ML models;
• one or more robotic process automation (RPA) robots configured to call at least one of the one or more AI/ML models during execution;
• and
• an action center, wherein
• the server is configured to:
• monitor performance of the one or more AI/ML models,
• receive a request from a calling RPA robot of the one or more RPA robots to execute an AI/ML model of the one or more AI/ML models, and
• when performance of the requested AI/ML model falls below one or more performance thresholds for a first time, over a time period, or over a number of runs of the requested AI/ML model, send a review request to the action center to review a result of the execution of the requested AI/ML model, and
• the action center is configured to:
• receive an indication from an action center application that the result is correct or receive a corrected result from the action center application, and
• when the result is incorrect, provide the corrected result from the action center to the calling RPA robot, to the server, or both.