Method and system for managing enterprise digital automation processes

An automation management system for managing enterprise digital automation processes, the automation management system comprising:

• a processor;
• and
• a memory, communicatively coupled to the processor, wherein the memory stores processor-executable instructions, which, on execution, causes the processor to:
• prioritize a plurality of automation requests, related to a plurality of enterprise digital automation processes, based on a criticality of each of the plurality of automation requests, historical resource utilization data and failure data related to one or more historical automation requests that are similar to the plurality of automation requests;
• select a plurality of tasks from a project application repository for executing the plurality of automation requests based on a type of the plurality of automation requests and execution requirements of the plurality of automation requests;
• monitor execution of the plurality of automation requests in real-time by generating a unified portfolio view of the plurality of tasks and by tracking a run-time cost and benefit for each of the plurality of tasks;
• generate in real-time, one or more alerts related to the execution of the plurality of automation requests based on a comparison between a real-time performance of the plurality of automation requests and one or more prestored Key Performance Indicators (KPIs);
• and
• optimize the execution of the plurality of automation requests by resolving each of the one or more alerts using a pretrained Artificial Intelligence (AI) model trained on one or more historical events associated with the plurality of automation requests.

A non-transitory computer readable medium including instructions stored thereon that when processed by at least one processor, cause an automation management system to perform operations comprising:

• prioritizing a plurality of automation requests, related to a plurality of enterprise digital automation processes, based on a criticality of each of the plurality of automation requests, historical resource utilization data and failure data related to one or more historical automation requests that are similar to the plurality of automation requests;
• selecting a plurality of tasks from a project application repository for executing the plurality of automation requests based on a type of the plurality of automation requests and execution requirements of the plurality of automation requests;
• monitoring execution of the plurality of automation requests in real-time by generating a unified portfolio view of the plurality of tasks and by tracking a run-time cost and benefit for each of the plurality of tasks;
• generating in real-time, one or more alerts related to the execution of the plurality of automation requests based on a comparison between a real-time performance of the plurality of automation requests and one or more prestored Key Performance Indicators (KPIs);
• and
• optimizing the execution of the plurality of automation requests by resolving each of the one or more alerts using a pretrained Artificial Intelligence (AI) model trained on one or more historical events associated with the plurality of automation requests.