For enterprise organizations, legacy core infrastructure is rarely just an engineering nuisance—it is an operational liability compounding quietly until vendor support deadlines force a crisis. When Microsoft set the end-of-life date for Xamarin, healthcare and insurance giant Bupa faced an uncomfortable reckoning with the stack powering its flagship My Bupa app. Asifa Sherazi, CIO of health insurance at Bupa, characterized the structural danger plainly, noting that deferring foundational overhauls allows technical debt to accumulate in silence until it suddenly threatens daily business continuity.
"The end-of-life technology is a risk that compounds quietly, and then arrives all at once."
In heavily regulated sectors like healthcare and insurance, kicking the technical debt can down the road is no longer viable when audit compliance and customer uptime hang in the balance.
Cutting Migration Timelines
Instead of greenlighting a high-risk, multi-year manual rewrite, Bupa partnered with Infosys to migrate My Bupa to native Swift and Kotlin environments via AI-assisted reverse and forward engineering. Sanjeev Tripathi, senior vice president and region head for BFSI and healthcare at Infosys, observed that generative models fundamentally break the traditional cost-risk equation of enterprise modernization, shrinking delivery schedules and engineering overhead without halting ongoing business operations.
This AI-accelerated workflow cut migration turnaround by roughly 60% compared to conventional legacy overhauls. However, converting legacy syntax is not an autonomous magic bullet: automated translation still demands rigorous domain audit of business logic, because an algorithm will happily translate thirty-year-old architectural flaws into modern, pristine syntax without fixing the underlying design errors.
Measurable Service Gains
The architectural overhaul delivered immediate operational validation rather than just theoretical efficiency. Shifting away from Xamarin to native mobile code pushed the My Bupa app store rating from 3.7 to 4.7 stars.
More critically for CIOs assessing uptime, the platform saw an immediate collapse in failure rates: user-perceived crash rates plunged by nearly 24 percentage points on Android and eight points on iOS. For enterprise leadership, AI-assisted migration marks a fundamental shift from perpetual crisis-containment to continuous, manageable architectural renewal.