Zero-touch transformation: AI-driven middleware for autonomous integration of legacy enterprise systems with cloud architectures

This abstract introduces a novel approach to enterprise legacy system migration through the development of Zero-Touch AI-driven middleware that autonomously facilitates the integration of aging enterprise infrastructures with modern cloud architectures. The proposed middleware employs advanced machine learning algorithms, natural language processing, and knowledge graphs to automatically discover, map, and optimize legacy workflows for cloud environments without manual intervention. The article demonstrates how this approach significantly reduces migration complexity, minimizes business disruption, and accelerates digital transformation initiatives compared to traditional migration methodologies. The article presents a theoretical framework, implementation architecture, and multiple case studies across financial services, manufacturing, and healthcare sectors that validate the efficacy of the Zero-Touch approach. Results indicate substantial improvements in migration timelines, cost efficiency, and post-migration system performance while addressing critical challenges in security, compliance, and edge cases. This research contributes to both theoretical understanding and practical implementation of AI-driven enterprise architecture transformation, offering a roadmap for organizations seeking frictionless modernization of their legacy systems.