Modernizing large enterprise codebases is no longer simply a matter of rewriting legacy applications in newer languages or moving workloads to the cloud. The harder problem is preserving business behavior, operational resilience, integration contracts, security controls, and decades of embedded domain knowledge while dramatically accelerating transformation.

This session presents a practical architecture for building an AI-driven software modernization factory for large, mission-critical systems.

Drawing on real-world experience modernizing enterprise financial platforms and applied research in AI-assisted software engineering, the session explores how generative and agentic AI can be introduced across the modernization lifecycle—from code understanding and dependency discovery to transformation, behavioral validation, integration testing, and production readiness.

The session will cover practical patterns for:

using AI to analyze and document large legacy codebases;
extracting business logic, dependencies, interfaces, and operational behaviors;
creating semantic representations that preserve system intent across modernization;
combining deterministic engineering controls with LLM-assisted code transformation;
validating behavioral equivalence between legacy and modern implementations;
introducing human review and policy gates into AI-generated software changes;
integrating security, observability, testing, and traceability into the modernization pipeline; and
scaling modernization across multiple applications without creating a new generation of technical debt.

A key focus will be the shift from using AI as a coding assistant to treating AI as part of a governed software factory—where models, agents, engineering tools, testing systems, security controls, and human experts operate within a repeatable modernization workflow.

Attendees will leave with a reference architecture and implementation framework for applying AI to enterprise modernization while preserving the reliability, traceability, and architectural discipline required for critical systems.