AI-powered self-adaptive middleware: Enabling Intelligent Enterprise IT Ecosystems

Aderu, Neelima (2025) AI-powered self-adaptive middleware: Enabling Intelligent Enterprise IT Ecosystems. World Journal of Advanced Research and Reviews, 26 (2). pp. 2960-2972. ISSN 2581-9615

AI-powered self-adaptive middleware represents a transformative approach to enterprise integration challenges, addressing the limitations of traditional middleware in increasingly complex IT ecosystems. This technological evolution enables organizations to overcome integration barriers that frequently derail digital transformation initiatives. By incorporating machine learning algorithms and intelligent automation, these next-generation systems continuously monitor environments, learn from patterns, and autonomously adjust configurations. The middleware provides dynamic load balancing, predictive fault detection, AI-driven resource allocation, and adaptive API management capabilities that significantly enhance operational efficiency. Additionally, these systems deliver robust fault tolerance through real-time anomaly detection, automated security policy enforcement, and self-correcting integration mechanisms. The technology demonstrates remarkable value across multiple sectors, including financial services, healthcare, supply chain and logistics, manufacturing, retail, and public sector. Organizations implementing these solutions experience enhanced integration efficiency, improved system resilience, reduced operational costs, accelerated time-to-market for digital initiatives, and superior compliance outcomes. As digital transformation accelerates, AI-powered middleware emerges as a critical enabler for creating adaptive, resilient enterprise architectures capable of navigating rapidly evolving technological landscapes while maintaining operational excellence.