Legacy Modernisation & Migration

Many organisations run critical systems on ageing technology - mainframe applications written in COBOL, monolithic systems built decades ago, databases running on unsupported platforms. Modernising these systems is expensive, risky, and often avoided until it becomes unavoidable. AI is beginning to help by analysing legacy codebases to understand what they do (often poorly documented after years of modifications), suggesting migration strategies, and even generating equivalent code in modern languages. AI tools can map the dependencies in complex legacy systems, identify the business rules embedded in old code, and create test suites to verify that migrated systems behave identically to the originals. This does not make legacy modernisation easy - it remains one of the hardest problems in enterprise IT - but AI can reduce some of the most painful aspects, particularly the archaeological work of understanding what legacy systems actually do. The risks include AI misinterpreting legacy code logic, generating modern code that is subtly different from the original, and the inherent difficulty of testing systems that may have evolved through decades of undocumented changes.