Contrary to conventional wisdom, MongoDB's CEO reveals enterprise leaders have a surprising appetite for full system replacement. An AI-native company that can replace an entire legacy system of record—making it cheaper, faster, and better—will get a leader's attention far more effectively than one offering an incremental feature layer on top of an existing platform.

To modernize its claims process, Unum first used AI to analyze 1.5 million lines of legacy COBOL code. They then fed this analysis into Pega Blueprint, effectively reverse-engineering the embedded business logic to visualize and create reimagined, modern workflows as a starting point for their transformation.

A logical data management layer acts as middleware, disintermediating business users from the underlying IT systems. This data abstraction allows business teams to access data and move quickly to meet market demands, while IT can modernize its infrastructure (e.g., migrating to the cloud) at its own pace without disrupting business consumption.

The initial step in modernizing is not to rebuild, but to understand. AI can ingest source code, user manuals, and even screen recordings to map existing processes and identify optimization opportunities, ensuring the new system improves upon the old rather than just replicating it.

AI-driven approaches dramatically reduce the time and cost of modernizing legacy systems. What was once a multi-year, multi-million dollar mainframe project can now be completed in as little as 90 days, fundamentally altering the ROI for tackling technology debt.

In a complex legacy environment, internal motivations like improving developer experience or modernizing technology often fail to gain traction. The initiatives that successfully navigate the process are those that can clearly articulate and deliver tangible value to the end customer.

For complex systems with diverse use cases (like EDI), building a comprehensive UI upfront is a failure path because you can't possibly anticipate all needs. The better approach is to first build a robust set of developer-focused APIs—like Lego blocks—that handle core functions. This allows you (and customers) to later assemble solutions without being trapped by premature UI decisions.

Instead of large, multi-year software rollouts, organizations should break down business objectives (e.g., shifting revenue to digital) into functional needs. This enables a modular, agile approach where technology solves specific problems for individual teams, delivering benefits in weeks, not years.

Even if legacy code is stable and functional, it should be replaced when the user experience it provides becomes obsolete. When user expectations (e.g., mobile access, modern UI) have fundamentally shifted, the old system becomes a liability regardless of its technical stability.