AI-CONVERGED COBOL MODERNIZATION
Understanding a COBOL system is only half the modernization problem. The next step — and the harder one — is turning that understanding into code that actually works.
Last month's session covered the strategy question — modernize, migrate, or rewrite. This month, we go one level deeper: what actually happens once an enterprise decides to transform COBOL into working Java microservices or Python — and how AI is changing that process from a risky, multi-year rewrite into a disciplined, structured pipeline.
In this session, we walk through how an AI-converged transformation agent moves from code understanding to code generation: extracting business rules and dependencies from decades-old COBOL, then generating target code in Java or Python that preserves exact COBOL semantics. Testing, validation, and deployment — proving that transformed code behaves identically to the original — will be the focus of upcoming sessions in this series.
What We'll Explore
Why “translate the code” was always the wrong first step
Reverse-engineering COBOL: recovering the specification the requirements doc lost
Building the dependency graph — programs, copybooks, JCL, and data flow
From business-rule extraction to a transformation-ready blueprint
Decide right modernization strategy
What way AI can support target as API, Java microservices vs. Python
What's actually working: real transformation outcomes, and where migrations still fail
From understanding to a working transformation: what you'll walk away with
From COBOL Code to a Working Transformation
See how an AI agent understands and transforms COBOL — end to end, through the Transform stage.
Discover
Identify the COBOL components in scope
Understand
Extract business rules and dependencies
Analyze
Map the call graph and risk areas
Recommend
Confirm the target: Java microservice or Python module
Transform
Generate translated code with AI assistance
The demonstration walks a real COBOL program through dependency mapping and business-rule extraction, then AI-assisted translation into a Java microservice — with its Python equivalent shown side by side — so you can see exactly how an AI agent turns understood COBOL logic into working target-language code.
Test, Deploy, and AIOps are covered in upcoming webinars in this series.
This is not simply a COBOL-to-Java demonstration.
It demonstrates how AI can turn decades of COBOL logic into working, modern code — with the proof and validation layer covered in our next session.
Built for Modernization Leaders
CIOs
CTOs
Enterprise Architects
Mainframe Leaders
Modernization Teams
Application Leaders
COBOL Professionals
DevOps Leaders
Digital Transformation Teams
From Roadmap to Reality
September focused on strategy, decisions, and the modernization roadmap. October turns that roadmap into working code — how AI understands and transforms COBOL into Java and Python. Testing, deployment, and continuous operations follow in upcoming sessions of this series.
Register for Webinar →October focuses on the transformation stage of the modernization journey.
From Strategy to the Code
September focuses on strategy, decisions and the modernization roadmap.
Strategy & Decisions
Explore how enterprises can make smarter modernization decisions and build a practical roadmap for their mainframe.
AI + COBOL in Practice
Move from strategy to the code itself with a deeper practical demonstration of AI-powered COBOL understanding and transformation.
Discover a Smarter Modernization Journey
Discover how AI can help transform decades of COBOL knowledge into a smarter, safer and more strategic modernization journey.
Register for the Webinar →
