| CPC G06N 20/00 (2019.01) [B25J 9/163 (2013.01); G06N 5/02 (2013.01)] | 20 Claims |

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1. A computer-implemented method for implementing a machine learning (ML) model retraining pipeline for robotic process automation (RPA), comprising:
calling a machine learning (ML) model, by an RPA robot, while executing an activity of an RPA workflow that uses the ML model;
receiving a result from the execution of the ML model, by the RPA robot;
completing execution of the activity of the ROA RPA workflow using the result from the execution of the ML model, by the RPA robot;
determining whether one or more trigger conditions are met for labeling of data for the ML model, by the RPA robot; and
responsive to the one or more trigger conditions being met:
prompting a user to provide labeled data for training or retraining the ML model and sending the labeled data to a server for training or retraining of the ML model, by the RPA robot, or adding information pertaining to the result from the ML model to a queue for subsequent labeling, by the RPA robot, wherein
the RPA workflow comprises a plurality of activities that comprise the one or more activities, and
the activities are a set of steps developed in the workflow.
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