Insights
Making the AI-powered case for legacy modernization
Legacy platforms often support an organization’s most important customer experiences. Yet the cost, complexity, and risk of transforming these systems can cause enterprises to defer modernization until technology constraints become business constraints.
In this episode of MIT Technology Review Insights’ Business Lab, Asifa Sherazi, CIO of Health Insurance at Bupa and Sanjeev Tripathi from Infosys, discuss how AI has changed the economics of modernization.
Asifa Sherazi
CIO of Health Insurance, Bupa
Sanjeev Tripathi
SVP and Region Head, Infosys
Their conversation explores Bupa Australia’s recent transformation of the My Bupa mobile application from Xamarin to native Swift and Kotlin. By combining AI-assisted reverse engineering with forward engineering, the program preserved critical business functionality while establishing a scalable, maintainable platform for faster innovation.
The result was not simply a technology migration. It was a business transformation designed to improve platform resilience, accelerate engineering, and make important digital services work more reliably for customers.
Measurable outcomes from the modernization
60% Less transformation time
The program was delivered in approximately 60% less time than would have been possible in the pre-AI era.
3.7 to 4.7 Improvement in app rating
The My Bupa app rating increased from 3.7 to 4.7 following the modernization.
4X Faster builds
Following launch, builds began completing four times faster, with code reaching testers in approximately one hour.
Zero High-severity and security defects at launch
AI-driven triage and predictive defect analysis were applied across nearly 1,400 cases, contributing to a launch with zero security defects and zero high-severity defects.
Listen to the full podcast on MIT Tech Review
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