Almost every established company has an outdated system governed by an unspoken rule: if it works, do not touch it. Yet that system is often both essential to day-to-day operations and an increasingly significant source of risk. The challenge with legacy software is that changing it is risky—but leaving it unchanged becomes progressively riskier too, says Raimo Seero, Chief Technology Officer at Uptime.
These systems may have been in use for years, sometimes decades. Everyone knows they are no longer modern and should be updated. But everyone also knows that even a minor change can break something elsewhere. In many cases, this ultimately means that the system is either left untouched—or that, at some point, the company decides to build an entirely new solution from scratch.
The rapid development of AI has changed this picture to some extent. Artificial intelligence can give legacy software a new lease of life. Until now, modernisation efforts have often been held back by the fear that no one fully understands what is happening within the code. With AI, that knowledge can be uncovered and made visible much faster—creating a practical starting point for software modernisation.
AI can, for example:
- analyse legacy code and identify how different parts of a system are interconnected;
- uncover business logic that has gradually become embedded in the code rather than documented;
- map risks, dependencies, and areas where a small change could lead to a major issue;
- prototype elements of a new solution more quickly, helping determine the most sensible modernisation path;
- support testing, making the impact of changes easier to manage and control.
AI makes it possible to examine an old system in a more structured and controlled way: to understand which processes are actually running, which rules have been built into the code over the years, and which parts of that knowledge can be transferred to a cleaner, more manageable platform.
Taking the Next Step Beyond Virtualisation
In the past, virtualisation solved a similar challenge. Companies had physical servers sitting in back rooms, each running a business-critical system. Everyone knew that if the last remaining old machine failed one day, it could cause serious disruption. Virtualisation extended the life of these systems by freeing the software from its dependence on specific physical hardware.
With the advancement of artificial intelligence, software whose code has become effectively untouchable over decades can now be given a similar extension to its useful life.
The fear of replacing legacy software is understandable. Keeping an old system running for one more year and hoping nothing goes wrong can seem like the most affordable option. But this is no longer necessarily the case: with AI, it is possible to create a new system based on existing software with far more reasonable cost and effort than before.
If your organisation has a system that everyone relies on but no one wants to change, it is already a business risk. Uptime can help assess whether—and how—AI can extend the useful life of that software. Together, we can review the system’s actual condition, uncover the processes and business rules hidden within it, and identify the most practical way forward.
Get in touch to find out whether AI can give your system a new lease of life—without exposing your business to unreasonable risk.
Why Consider Modernising Legacy Software?
- Large companies often spend up to 70% of their IT budgets maintaining existing systems rather than developing new solutions.
- Documentation for older systems is often outdated or incomplete, meaning critical business logic may exist only in legacy code.
- Every postponed modernisation effort adds to technical debt, making future changes more expensive and riskier.
- AI can analyse thousands of lines of legacy code in minutes, helping teams understand system dependencies and risk areas more quickly.
- Modernisation no longer necessarily means rebuilding everything from scratch. With AI, existing systems can be upgraded gradually and developed further in a controlled manner.
