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Stream/Area:
-
Subject:
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Paper ID:
IJSREM64677
Volume:
10 |
6 |
Jun 2026
Pages:
1-19
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

Department of Computer Networking
PSG POLYTECHNIC COLLEGE
Department of Computer Networking
PSG POLYTECHNIC COLLEGE
Department of Computer Networking
PSG POLYTECHNIC COLLEGE
Department of Computer Networking
PSG POLYTECHNIC COLLEGE
Department of Computer Networking
PSG POLYTECHNIC COLLEGE
Department of Computer Networking
PSG POLYTECHNIC COLLEGE
Department of Computer Networking
PSG POLYTECHNIC COLLEGE
Department of Computer Networking
PSG POLYTECHNIC COLLEGE
Department of Computer Networking
PSG POLYTECHNIC COLLEGE
The rapid advancement of Artificial Intelligence (AI) has significantly transformed the development of modern web applications by enabling intelligent automation, personalized user experiences, and data-driven decision-making. The MERN Stack, consisting of MongoDB, Express.js, React.js, and Node.js, has emerged as a popular framework for building scalable and efficient full-stack web applications. This research explores the integration of Artificial Intelligence within MERN Stack applications to enhance functionality, performance, and user engagement. The proposed framework combines AI-powered modules such as conversational chatbots, recommendation systems, intelligent search engines, predictive analytics, and automated content generation with the MERN architecture. The study examines the architectural design, implementation methodology, and interaction between AI services and web application components. Furthermore, the research analyzes the advantages, challenges, and practical applications of AI-enabled MERN systems across various domains. Experimental evaluation indicates that AI integration improves application responsiveness, personalization, automation, and overall user satisfaction. The findings demonstrate that the combination of Artificial Intelligence and MERN technologies provides a scalable and intelligent framework for developing next-generation web applications capable of meeting modern digital requirements.
KEYWORDS
The integration of Artificial Intelligence technologies within the MERN Stack framework provides a powerful approach for developing intelligent, scalable, and user-centric web applications. This research presented a comprehensive framework that combines MongoDB, Express.js, React.js, and Node.js with advanced AI functionalities such as recommendation systems, chatbot services, intelligent search mechanisms, and predictive analytics. The proposed framework demonstrates how modern web development technologies can be enhanced through Artificial Intelligence to improve application performance, user engagement, and decision-making capabilities. The implementation and evaluation of the framework highlighted several advantages including intelligent automation, personalized user experiences, scalability, flexibility, and data-driven decision-making. The results obtained from the study indicate that AI-powered services can significantly improve the effectiveness of web applications by providing adaptive and intelligent functionalities. The modular architecture of the MERN Stack further supports seamless integration of AI technologies while ensuring maintainability and future scalability. Furthermore, the study identified important challenges and limitations related to data privacy, computational requirements, integration complexity, and model reliability. Despite these challenges, the findings demonstrate that the benefits of AI integration outweigh the associated limitations when appropriate design strategies and security measures are implemented. The framework provides a strong foundation for organizations seeking to develop intelligent applications capable of meeting modern technological demands. In conclusion, the proposed AI-integrated MERN framework successfully demonstrates the potential of combining Artificial Intelligence with modern web development practices. The framework offers a scalable, flexible, and future-ready solution that can be applied across multiple domains including healthcare, education, e-commerce, finance, and business management. Future advancements in Artificial Intelligence, cloud computing, edge computing, and emerging technologies are expected to further enhance the capabilities of such systems and support the development of next-generation intelligent web applications.
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Publication Date
6/9/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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The authors declare no conflict of interest related to this research work.
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