Enterprise Application Modernization Using Agentic AI and Generative AI

Abstract

The modernization of enterprise applications is becoming increasingly vital for companies wishing to enhance agility, scalability, and efficiency in today’s rapidly changing digital landscape. The current research focuses on the use of Agentic AI and Generative AI in the modernization of legacy enterprise applications in the form of intelligent automation and autonomous decision-making. Qualitative research design was applied through the use of secondary sources consisting of peer-reviewed journal articles and industry publications. Inductive approach and thematic analysis methods were used to identify significant patterns in relation to AI-based modernization. It was found that Generative AI speeds up code transformation, refactoring, automated testing, documentation, and technical debt reduction. Consequently, it helps to achieve faster and more efficient modernization of software applications. Agentic AI contributes to the modernization of enterprises through orchestration of autonomous workflows, integration of legacy and cloud-native systems, and decision-making. Performance, scalability, predictability, and resource management in the organization will improve due to AI-driven modernization, resulting in increased business agility and reduced operational costs. Some of the other challenges faced while implementing AI technology include those related to governance, security, explainability, data privacy, organizational readiness, and skill gaps among employees. Appropriate governance frameworks, human interaction, cloud computing, and continued skills development are required to ensure the ethical utilization of artificial intelligence technology. Agentic AI and Generative AI technology offer a good starting point for the modernization of enterprise applications by cutting down on technical debts, building resiliency, and promoting digital innovation continuously.