One of the areas where AI can create immediate impact is application modernization. Migrating enterprise Java applications between major JDK versions is often a time-consuming effort involving dependency updates, compatibility checks, testing, and validation.
That's why this feedback from Sai Govender, CEO of Blue Pearl, caught my attention.
"We leveraged BOB to modernise Java codebase from Java 11 to Java 25 and achieved an estimated ~90% faster delivery: 3 days vs. ~30+ days via a typical approach. The outcome was genuinely impressive and has opened multiple use cases for Blue Pearl to incorporate IBM BOB across our internal platforms as well as client engagements.”"
What's interesting here isn't just the speed improvement. Large-scale Java upgrades are frequently postponed because of the effort involved and the risk of introducing issues into production systems. Having an AI development partner that can assist with modernization workflows can help teams move these initiatives forward with greater confidence.
The feedback also highlights a broader trend. AI is increasingly being used not only for writing new code, but for upgrading, maintaining, and evolving existing applications. For organizations with significant legacy estates, that may be where some of the biggest opportunities exist.
The future of AI in software development may be less about generating code from scratch and more about helping teams modernize faster, reduce technical debt, and keep systems current.
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