AI Driven Intelligent Accessibility Optimization for Large Scale Enterprise Web Systems using Cloud Architectures
Abstract
This scholarly paper aims at providing an artificial intelligence solution in order to get accessibility of the enterprise web systems optimized to large sizes under cloud structures. The proposed model will involve machine learning and intelligent automation to detect and address the dynamically emerging access issues in tricky web situations. The system monitors the elements of the web constantly, builds on user interaction data and applies adaptive additions to fulfill the needs of accessibility, including WCAG, with the capability of scale out in a cloud environment. The framework has various main elements, such as an AI-powered accessibility assessment engine, a real-time remediation module, and a cloud-based layer of orchestration to control the distribution of resources and system performance. The strategy will enable businesses to have a high performing site with minimal human intervention and making the site more accessible to individuals with disabilities. The outcomes of experimental testing lead to a great improvement of accessibility scores, as well as responsiveness of the system in case of the enterprise web platforms. The results of this study demonstrate how AI solutions and cloud computing may apply to fulfill the growing demand to provide inclusive and in large volumes digital services.
Article Information
Journal |
International Journal of Science, Research and Technology |
|---|---|
Volume (Issue) |
Vol. 8 No. 3 (2025): International Journal of Science, Research and Technology (IJSRAT) |
DOI |
|
Pages |
14222-14232 |
Published |
June 18, 2025 |
| Copyright |
All rights reserved |
Open Access |
This work is licensed under a Creative Commons Attribution 4.0 International License. |
How to Cite |
Dr.R.Sugumar (%2025). AI Driven Intelligent Accessibility Optimization for Large Scale Enterprise Web Systems using Cloud Architectures. International Journal of Science, Research and Technology , Vol. 8 No. 3 (2025): International Journal of Science, Research and Technology (IJSRAT) , pp. 14222-14232. https://doi.org/10.15662/IJSRAT.2025.0803003 |
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