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Main Author: Agrawal, Neeraj
Format: Recurso digital
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Published: Zenodo 2026
Online Access:https://doi.org/10.5281/zenodo.18446294
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author Agrawal, Neeraj
author_facet Agrawal, Neeraj
contents <p>The modernization of legacy core systems is a strategic imperative for enterprises seeking agility, scalability, and resilience in the digital era. However, the decoupling and containerization of monolithic architectures remain complex, resource-intensive, and risk-prone. This paper explores how artificial intelligence (AI) can be harnessed to accelerate and de-risk this transformation. By integrating AI into code analysis, dependency mapping, automated refactoring, and orchestration, organizations can streamline modernization efforts and unlock cloud-native capabilities. Drawing from industry case studies and emerging research, we propose a framework for AI-assisted core modernization and examine its implications for enterprise architecture, governance, and operational excellence.</p>
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spellingShingle Leveraging AI to Accelerate Decoupling and Containerization of Core Systems
Agrawal, Neeraj
<p>The modernization of legacy core systems is a strategic imperative for enterprises seeking agility, scalability, and resilience in the digital era. However, the decoupling and containerization of monolithic architectures remain complex, resource-intensive, and risk-prone. This paper explores how artificial intelligence (AI) can be harnessed to accelerate and de-risk this transformation. By integrating AI into code analysis, dependency mapping, automated refactoring, and orchestration, organizations can streamline modernization efforts and unlock cloud-native capabilities. Drawing from industry case studies and emerging research, we propose a framework for AI-assisted core modernization and examine its implications for enterprise architecture, governance, and operational excellence.</p>
title Leveraging AI to Accelerate Decoupling and Containerization of Core Systems
url https://doi.org/10.5281/zenodo.18446294