This study investigates the integration of Natural Language Processing into Management Information Systems and its contribution to business innovation, marketing responsiveness, and strategic decision-making. The exponential growth of unstructured data from social media, financial reports, and customer feedback requires firms to adopt intelligent tools beyond traditional MIS. By incorporating NLP, organizations convert raw textual data into strategic insights for competitor analysis, supplier risk assessment, misinformation detection, and contextual business intelligence. This research aims to explore how NLP-enabled MIS improves supply chain resilience, facilitates data-driven strategies, and enhances overall organizational performance. A qualitative literature review was conducted by synthesizing peer-reviewed journals, conference proceedings, and industry reports published between 2020 and 2025. The results show that NLP strengthens sentiment analysis, named entity recognition, and automated summarization, enabling managers to react quickly to market dynamics and safeguard corporate reputation. Nevertheless, major challenges persist, including system incompatibility, high implementation costs, limited digital literacy, and cybersecurity risks. Success factors rely strongly on top management support, effective communication, quality assurance, and employee readiness. The study concludes that the NLP-MIS synergy represents a strategic resource for achieving sustainable competitive advantage when properly aligned with organizational objectives and human capital development.