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@article{191547,
        author = {Sarath Vankamardhi nirmala varadhi},
        title = {Micro-Frontend Architectures Enabling AI-Powered Enterprise Web Applications},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {8},
        pages = {8433-8441},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=191547},
        abstract = {The increasing demand for scalable, modular, and intelligent enterprise web applications has driven the convergence of two powerful paradigms: micro-frontend architectures and AI-powered services. This review explores how micro-frontends, as an extension of microservices to the frontend layer, enable domain-driven development and team autonomy in large-scale web systems. We critically examine the integration of AI models into distributed frontend components, evaluating architectural strategies, performance trade-offs, deployment models, and developer workflows. Through theoretical modeling, experimental evaluation, and analysis of real-world systems, the study identifies key benefits—such as reduced latency, enhanced modularity, and improved user experience—as well as ongoing challenges, including model governance, security, and tooling maturity. The paper concludes by outlining future research directions that could standardize and accelerate the adoption of AI-enhanced micro-frontend architectures across enterprise contexts.},
        keywords = {Micro-Frontend Architecture, Enterprise Web Applications, Artificial Intelligence, MLOps, Frontend Modularization, Model Management, User Personalization, AI Deployment Strategies, and Scalability in Web Systems.},
        month = {January},
        }