How is AI changing COBOL system modernization?

AI is automating COBOL code exploration, dependency mapping, and risk analysis, significantly reducing the time and cost of modernizing legacy systems.

How does AI help prioritize COBOL modernization?

AI analyzes structural relationships to help engineers prioritize which components to modernize first based on technical risk and business value.

Can AI verify that migrated COBOL code works correctly?

Yes, AI can generate preliminary function tests to verify that newly migrated code produces identical outputs to the original legacy system.

Home / Technology / AI Revolutionizes COBOL Modernization

AI Revolutionizes COBOL Modernization

28 Feb

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Summary

AI now automates COBOL code exploration and dependency mapping.
Engineers can now prioritize modernization based on risk and value.
Automated tests ensure migrated code matches legacy outputs precisely.

Hundreds of billions of lines of COBOL code continue to power critical global systems, yet the scarcity of developers familiar with this legacy technology has long hindered modernization efforts. This has historically resulted in costly, labor-intensive projects requiring extensive human analysis of workflows and dependencies.

Anthropic's Claude AI is now poised to automate much of this challenging exploration phase. The AI can map intricate dependencies across vast codebases, trace data flows, and document complex workflows, identifying structural risks and fragile code components. This analysis enables engineers to strategically prioritize modernization efforts based on technical risk and business value.

AI tools can also translate COBOL logic into modern languages and create API wrappers, allowing legacy and new code to coexist. Automated tests verify that migrated components function identically to the original systems. While AI provides comprehensive insights, final decisions on modernization sequences remain with human judgment, ensuring strategic alignment with business and regulatory needs.

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