The Use of Natural Language Processing in MIS for Automating Business Processes

Abstract

This study explores the transformative potential of integrating Natural Language Processing (NLP) into Management Information Systems (MIS) to automate business processes. Employing a systematic review methodology, we analyzed 40 peer-reviewed studies to synthesize insights on NLP's role in data extraction, real-time analytics, and decision support. Key findings highlight the efficiency of NLP-powered systems in processing unstructured data and the advancements enabled by transformer-based models like BERT and GPT. While the integration of NLP in MIS offers unprecedented opportunities for innovation and operational agility, challenges such as data privacy, algorithmic bias, and computational resource demands persist. This research underscores the need for ethical frameworks and domain-specific NLP models to ensure responsible and effective implementation. The findings contribute to a deeper understanding of NLP's capabilities in shaping the future of MIS and its applications in diverse organizational contexts.