Technical debt in legacy applications: when does it start holding back business growth?

In many organizations, technical debt does not appear in financial reports or on the CIO dashboard. It shows up elsewhere: a new feature that was supposed to take two weeks ends up taking two months. Integration with a new tool turns into a quarter-long project. A simple change requires the involvement of specific experts because only they truly know how the system works.

The paradox is that the application still works. It supports customers, orders, reporting, and operational processes. The problem is that it stops evolving alongside the business and starts limiting it.

According to Gartner, global IT spending reached USD 5.43 trillion in 2025, representing approximately 7.9% growth compared to the previous year. Companies are investing more and more in technology, yet a substantial portion of these budgets continues to be absorbed by maintaining environments that, rather than supporting growth, increasingly slow it down.

Technical debt is the cost of decisions made in the past: implementation shortcuts, postponed updates, missing documentation, business workarounds, or solutions that were sufficient in the past but now hinder development.

It does not always stem from mistakes. It often develops naturally as a system adapts over the years to new processes, integrations, regulations, and user expectations. Therefore, the issue is not the age of the application itself, but rather that the organization loses control over its complexity, costs, and the associated risks.

Legacy applications are older systems that continue to support critical business processes but are difficult to maintain, develop, or integrate with modern IT environments. They may be stable, but every change requires increasing effort.

Most often, it results from time pressure. A company needs a quick change, so the team adds another feature. Then a new integration appears, a business exception is introduced, or a process is carried out partly manually. Each decision is justified at the time, but over the years their consequences begin to accumulate.

After years of development, a legacy application becomes a mosaic of technical and business decisions. This is compounded by a lack of up-to-date documentation, knowledge hidden in the code or in the minds of a few individuals, and dependence on technologies for which specialists are increasingly difficult to find.

In modernization projects, the biggest challenge is rarely the code itself. More often, the difficulty lies in dependencies between systems, business logic, and the lack of complete knowledge of which elements are truly critical to the business.

From a business perspective, the most important signs are those visible in day-to-day operations:

• every change takes longer and longer,
• simple fixes cause errors in other areas of the system,
• deployments require extensive manual testing,
• documentation is outdated or nonexistent,
• integrations are unstable,
• reports are generated with delays,
• employees rely on manual workarounds,
• the company becomes dependent on a few specific specialists.

What are often dismissed as “normal IT issues” are, in reality, signs that technical debt is beginning to impact the operational efficiency of the entire organization.

Practical example

For an international media group, we carried out a modernization project for a marketing platform based on the no longer supported .NET Framework 4.8. The system was affected by performance issues, limited scalability, and a growing maintenance backlog. The modernization enabled us to prepare the platform for further development and new integrations.

The line is crossed when system limitations begin to influence business decisions. The company does not launch a new service because the system cannot support the process. It does not automate customer service because data is scattered. It does not integrate a new tool because the architecture does not allow it. It does not plan cloud migration because no one knows what dependencies exist within the current environment.

At this point, the cost of technical debt is no longer just developer time. The cost becomes lost opportunities: slower time-to-market, more difficult business scaling, greater risk of failures, and a less predictable IT budget.

This is why discussions about technical debt should interest not only CTOs and CIOs, but also system owners, operations directors, and executive boards.

Practical example

For one of our clients, a company developing an IoT platform, the key challenge was an outdated system that had evolved for years without a consistent architectural vision. Its modernization enabled the creation of a solution that was easier to develop and integrate, while better supporting business scalability in line with rapidly changing needs.

Because it rarely appears as a separate item in the budget. It is hidden in longer implementation times, an increased number of fixes, manual testing, downtime, maintenance of outdated environments, and the costs of hiring specialists in obsolete technologies.

There are also indirect costs: user frustration, slower customer service, delayed business decisions, and lack of access to up-to-date data. Therefore, the first step should not be automatically rewriting the system from scratch. Instead, it is worth assessing the true scale of the problem the organization is facing.

A good starting point is a legacy application audit. It allows the assessment of code, architecture, documentation, data, integrations, security, performance, and maintenance processes. It is the best first step before modernization, migration, or rebuilding a system.

As part of the audit, technical debt itself is also analyzed, including the areas that increase maintenance costs and hinder system development. The result is a risk map, a list of priorities, and recommended courses of action.

Not every legacy application needs to be replaced:

• Refactoring allows the codebase to be improved without changing the system’s functionality.
• Modernization may involve redesigning the architecture or selected application components.
• IT system migration involves moving applications, data, or processes to a new technological environment.

In many organizations, a phased approach delivers the best results: first diagnosis and audit, then improvement of the most critical areas, and only afterward broader transformation. Depending on business needs, the next step may also include IT system migration, migration to the Azure cloud, or broader cloud migration initiatives.

Reducing technical debt does not have to mean freezing system development for months.

The process most often includes:

• Prioritizing the most important areas.
• Modernizing the system module by module.
• Expanding automated testing.
• Organizing and updating documentation.
• Stabilizing integrations between systems.

AI-powered tools are also increasingly being used to support these efforts. They can assist in analyzing code, documentation, and dependencies, helping accelerate the preparation of modernization projects. More about this topic in the article: How does AI support the modernization of legacy applications?

When maintenance costs continue to rise, implementing changes takes increasingly longer, the system hinders integrations, or the company is planning a digital transformation or cloud migration.

The best time to act is before a system failure occurs, before key specialists leave and take critical knowledge with them, or before an urgent system replacement becomes necessary.

Technical debt does not have to mean an expensive revolution. However, it does require diagnosis, clear priorities, and a plan of action. Only then can an organization consciously decide whether refactoring, modernization, or migration is the best course of action.