INTEGRATING FUZZY LOGIC AND ARTIFICIAL INTELLIGENCE IN OPTIMIZING BUSINESS PROCESS AUTOMATION DECISIONS

Abstract

The paper explores the application of artificial intelligence methods for optimizing business decision-making processes in enterprises. The main focus is on the development of an intelligent fuzzy model for selecting a platform for robotic process automation (RPA) in trade and manufacturing companies. The purpose of the research is to increase the efficiency and justification of managerial decisions during the implementation of RPA technologies under uncertainty. The proposed model is based on fuzzy logic and the mechanism of fuzzy inference and has been implemented in the FuzzyTECH software environment. The model includes three groups of parameters describing the functional, security, and accessibility characteristics of RPA platforms. A comparative evaluation of five major RPA platforms—PIX Robotics, Primo RPA, Robin, Sherpa RPA, and ROOMY bots—has been conducted. The results show that the developed fuzzy model provides a clear and reliable assessment of platform compliance with enterprise requirements and can be used as a decision support tool when selecting RPA vendors. The practical significance of the work lies in the possibility of applying the model to analyze and optimize processes in various industries.