Predictive healing artificial intelligence agents that preemptively detect impending workflow errors, failures, and/or faults and automatically attempt recovery

A computer-implemented method, comprising:

• starting an agentic loop, by a computing system, for a healing artificial intelligence (AI) agent that comprises monitoring an object repository using a generative AI model, the generative AI model fine-tuned using data stored in the object repository;
• determining, by the healing AI agent, that one or more changes have occurred in the object repository that will affect a workflow of a robotic process automation (RPA) robot, another AI agent, or an agentic orchestration process (AOP) using the generative AI model;
• and
• attempting to repair the workflow using the generative AI model, by the healing AI agent.

One or more computing systems, comprising:

• memory storing computer program instructions;
• and
• at least one processor configured to execute the computer program instructions, wherein the computer program instructions are configured to cause the at least one processor to:
• start an agentic loop for a healing artificial intelligence (AI) agent that comprises monitoring an object repository using a generative AI model, the generative AI model fine-tuned using data stored in the object repository,
• determine that one or more changes have occurred in the object repository that will affect a workflow of a robotic process automation (RPA) robot, another AI agent, or an agentic orchestration process (AOP) using the generative AI model,
• attempt to repair the workflow using the generative AI model,
• responsive to the attempted workflow repair being successful, send the repaired workflow to a conductor application to deploy the repaired workflow to one or more computing systems on which the RPA robot, the other AI agent, or an AOP engine that executes the workflow is deployed, and
• responsive to the attempted workflow repair not being successful, collect data pertaining to the one or more changes and send the collected data to a human-in-the-loop and/or to one or more computing systems that are configured to retrain the generative AI model.