AI-DRIVEN CASE MANAGEMENT IN ELICENSING / EPERMITTING: IMPLEMENTATION, IMPACT, AND INNOVATION

Abstract

This article presents a comprehensive framework for integrating artificial intelligence into eLicensing / ePermitting support systems, addressing the growing need for efficient case management in regulatory environments. The proposed solution leverages advanced natural language processing and machine learning techniques to create an intelligent assistant that augments human support agents rather than replacing them. By automating routine tasks such as information gathering, documentation, and case routing, the system significantly streamlines the licensing process while maintaining high standards of accuracy and compliance. This article demonstrates how AI can be effectively deployed to handle complex regulatory workflows while preserving the crucial element of human oversight. The implementation results indicate substantial improvements in case resolution times, agent productivity, and overall user satisfaction. This article contributes to the emerging field of AI-assisted regulatory technology, offering insights into practical applications of machine learning in government services and suggesting pathways for future development in automated compliance systems.