AI-POWERED MAINFRAME APPLICATION MODERNIZATION: A TECHNICAL PERSPECTIVE

Abstract

This article explores the transformative role of Artificial Intelligence in modernizing legacy mainframe systems within enterprise environments. As organizations face increasing pressure to evolve their critical infrastructure while maintaining operational continuity, AI technologies emerge as pivotal solutions in addressing modernization challenges. The article examines how deep learning algorithms, machine learning models, and natural language processing capabilities revolutionize code analysis, system optimization, and documentation processes. The article demonstrates how AI-driven approaches significantly reduce modernization timelines, migration costs, and overall system quality in a comprehensive article that covers implementation strategies, benefits, and challenges. The article also investigates current challenges in data quality, system complexity, skill gaps, and change management, proposing mitigation strategies and exploring future perspectives, including quantum computing applications and extended automation capabilities. The article suggests that AI-driven modernization represents a paradigm shift in legacy system transformation, offering organizations a pathway to enhanced agility and innovation in the digital era.