Intelligent Legacy System Modernization: A Framework for Automated Application Migration using AI/ML/GenAI/LLM
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Abstract
In today’s rapidly evolving digital landscape, modernizing legacy systems is imperative for organizations to remain competitive and agile. This study introduces an innovative framework titled “Intelligent Legacy System Modernization: A Framework for Automated Application Migration using AI/ML/GenAI/LLM.” The framework leverages advanced artificial intelligence (AI), machine learning (ML), generative AI (GenAI), and large language models (LLM) to facilitate the seamless migration and modernization of outdated software systems. By integrating these cutting-edge technologies, the proposed solution automates the migration process, reduces manual intervention, and minimizes the risks associated with legacy system dependencies. The framework is designed to analyze, interpret, and transform legacy codebases into modern architectures, ensuring enhanced performance, scalability, and maintainability. Furthermore, it incorporates predictive analytics to foresee potential issues during migration, enabling proactive problem-solving. Through a series of experiments and case studies, the framework demonstrates significant improvements in migration speed and cost efficiency, while maintaining high levels of accuracy and system reliability. This research also highlights the challenges encountered during the integration of AI/ML tools in legacy environments and offers strategies to overcome these obstacles. Overall, the proposed intelligent modernization framework not only optimizes application migration processes but also provides a robust foundation for future technological advancements, ensuring that legacy systems can evolve in tandem with emerging digital innovations.
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