Leveraging AI for Dynamic Data Schema Adaptation in Agile Development Frameworks

Abstract

In today’s fast-paced development environments, agility and flexibility are paramount. The rapid evolution of requirements and data structures necessitates a robust mechanism for adapting data schemas in real time. This paper explores how artificial intelligence (AI) can be leveraged for dynamic data schema adaptation within agile development frameworks. By analyzing existing methodologies, tools, and case studies, we propose a framework that incorporates AI-driven techniques for optimizing data schema evolution, thereby improving development efficiency, reducing errors, and enhancing data integrity.