Leveraging multiple disparate machine learning model data outputs to generate recommendations for the next best action

A system for determining a priority service context specific (SCS) channel among multiple SCS channels according to a priority status metric (PSM) and sending an advisory message thereto, the system comprising:

• at least one processor;
• a communication interface communicatively coupled to the at least one processor;
• and
• a memory device storing executable code that, when executed, causes the processor to:
• monitor signals in multiple bidirectional SCS channels between multiple system devices and at least one user device, each SCS channel conveying signals to and from a respective system device of the multiple system devices;
• identify, using an algorithm trained by a machine-learning technique, a respective PSM for each SCS channel;
• determine a priority SCS channel having a PSM higher than at least some of the other SCS channels;
• generate an advisory message for the priority SCS channel;
• and
• send the advisory message to the respective system device of the priority SCS channel,
• wherein, via each of the multiple SCS channels, at least one system device communicates with a user of the at least one user device via a respective human agent or virtual agent using conversational artificial intelligence (AI), and wherein the advisory message guides the human agent or virtual agent of the priority SCS channel in a system-wide next dialog with the user.

A method for determining, by a computing system, a priority service context specific (SCS) channel among multiple SCS channels according to a priority status metric (PSM) and sending an advisory message thereto, the system comprising at least one processor, a communication interface communicatively coupled to the at least one processor, and a memory device storing computer-readable instructions, the at least one processor configured to execute the computer-readable instructions, the method comprising, upon execution of the computer-readable instructions by the at least one processor:

• monitoring signals in multiple bidirectional SCS channels between multiple system devices and at least one user device, each SCS channel conveying signals to and from a respective system device of the multiple system devices;
• identifying, using an algorithm trained by a machine-learning technique, a respective PSM for each SCS channel;
• determining a priority SCS channel having a PSM higher than at least some of the other SCS channels;
• generating an advisory message for the priority SCS channel;
• and
• sending the advisory message to the respective system device of the priority SCS channel,
• wherein, via each of the multiple SCS channels, at least one system device communicates with a user of the at least one user device via a respective human agent or virtual agent using conversational artificial intelligence (AI), and wherein the advisory message guides the human agent or virtual agent of the priority SCS channel in a system-wide next dialog with the user.