So while AI investments continue to grow within the software development lifecycle (SDLC), old software won’t soon become obsolete. This definitely makes it easier to tune, update, test legacy applications, and in some cases, enable complete migration to modern platforms. And the truth is, this is not a new phenomenon. Companies have always sought to increase efficiency and squeeze profits from existing products through intelligent prioritization.
This means that CIOs and CTOs can proactively consider their legacy application portfolios to determine which, if any, need to be migrated sooner. Five considerations will help you make that decision.
Ask these 5 important questions before replacing your legacy apps with AI
1. Will my legacy applications still work?
Does its usefulness still remain? Customers often value the consistency of legacy applications. They are reliable, predictable, and well understood. There’s no need to fix what isn’t broken. Another way to think about this is technical approach Legacy applications can still run. With today’s software, it’s almost guaranteed that an application built one way using some technology will be built very differently just a few years later. While you can’t avoid this, what you want to avoid is investing more in technological approaches to enhance legacy applications that have been completely replaced by new software or technological approaches. Especially when it’s 10x better across software development vectors (latency, cost, accuracy).
