Prompt-robotics: Leveraging Large Language Model (llm) Agents to Enhance Robotic Process Automation (rpa) Supervision and Efficiency
Year: 2025
Type: article
Abstract: Robotic Process Automation (RPA) has become one of the revolutionary technologies in its quest to streamline business processes by automating repetitive and rule-based processes.Although adopted in various industries, traditional RPA systems are still limited in flexibility, unable to work with unstructured data, and over-dependent on human supervisors in cases of exceptions.These issues make performance less efficient and less scalable in dynamic environments.Recent advances in Large Language Models (LLMs) offer an avenue to overcome these shortcomings, since LLMs can provide superior natural language processing, contextual reasoning, and adaptive decision-making.In this work, the authors present Prompt-Robotics, a new model based on incorporating LLM agents into RPA pipelines to improve supervision, error detection, and process optimization.It uses the techniques of prompt engineering to control execution, dynamically reschedule workflows, and allow smart resolution of anomalies in the framework.The possible benefits of LLM-augmented RPA are demonstrated with the help of simulated scenarios in the finance, customer service, and Saurabh Kakkar https://iaeme.com/Home/journal/IJFDS 8
Author: Saurabh Kakkar
Language: English
Subfield: Industrial and Manufacturing Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
OpenAlex ID: W4414092067