Legacy System Integration: How to Connect Old Systems Without Replacing Them

The US federal government spends more than USD 100 billion a year on IT, and agencies typically report spending about 80% of it on operating and maintaining existing systems, according to a July 2025 report from the Government Accountability Office. Of ten critical legacy systems the GAO flagged for modernization in 2019, three had been modernized by February 2025. Replacing a legacy system is slow, expensive, and risky, so most organizations live with these systems for years and connect them to everything new instead. This guide covers what legacy system integration involves, the main ways to do it, which approach fits which goal, when to integrate and when to replace, and what usually goes wrong.

What is legacy system integration?

Legacy system integration is the work of connecting an older system that the business still depends on to newer applications, data platforms, or AI tools, so data and processes can flow between them without replacing the old system. Typical examples are a mainframe holding customer accounts, an old ERP running finance, or a decades-old database behind a core operation.

Age alone does not make a system “legacy.” The GAO’s 2025 review scored systems on attributes such as age, vendor support, use of legacy programming languages, cybersecurity risk, and operating cost. In practice, a system becomes legacy when it is hard to change, hard to connect, or hard to find people for, while the business still cannot run without it.

Why are legacy systems still so widespread?

Legacy systems persist because they run critical operations reliably, and replacing them carries real risk to the business. In many organizations their use is growing, not shrinking, even as everything around them modernizes.

• Modernization is slow even when it is a priority. The GAO’s 2025 review of 69 federal legacy systems found 11 most in need of modernization. Eight use outdated languages, four run on unsupported hardware or software, and seven have known cybersecurity vulnerabilities. Two of them, at the Treasury, run on COBOL and Assembly.
• Use keeps growing. In Kyndryl’s 2025 survey of 500 business and IT leaders at organizations that use mainframes, 56% reported increased use of the platform in the past year. Kyndryl sells mainframe services, so read the survey with that in mind.
• Connections lag behind. MuleSoft’s 2025 research found the average organization runs 897 applications and connects only 29% of them. Legacy systems are often among the hardest to connect, which makes them a common cause of siloed data.

What are the main ways to integrate a legacy system?

There are six common ways to integrate a legacy system, from simple scheduled file exports to real-time event streams. The right one depends on how fresh the data needs to be, whether other systems need to write back to the legacy system, and what the legacy system can technically support.

Approach	How it works	Best for	Watch out for
Scheduled file or batch exports	The legacy system writes files on a schedule; a pipeline loads them elsewhere	Reporting and analytics that can tolerate daily or hourly data	Stale data, fragile file formats, silent failures
Database replication or change data capture	Changes in the legacy database are copied to a modern platform as they happen	Near-real-time analytics without touching the application	Load on the legacy database, schemas that are poorly documented
API layer	A modern API is built in front of the legacy system and translates requests	New applications that need to read from or write to the legacy system	Performance limits of the system behind it, keeping the API secure
Middleware or integration platform	A central platform connects many systems through prebuilt connectors	Organizations with many systems to connect	Platform cost, a new dependency in the middle of everything
Event streaming	The legacy system’s changes are published as events other systems subscribe to	Real-time operations across several systems	Engineering effort and skills, harder to set up on older platforms
Screen automation (RPA)	Software robots use the legacy system’s screens like a person would	Last resort when no data or API access exists	Breaks when screens change, slow, hard to scale

Most organizations end up using several of these at once. The point is to choose each one deliberately for a specific need, rather than adding a new connection type every time a project asks for data.

Which integration approach fits which goal?

Start from what the integration is for. Getting legacy data into reports, feeding it to AI, and letting new applications act on the legacy system are three different problems, and each points to a different approach.

• Reporting and analytics. Batch exports or change data capture into a central data platform are usually enough. The data then needs transformation into a usable shape, and often harmonization, because legacy systems frequently define customers, products, or accounts differently from newer ones.
• AI and machine learning. AI needs the same data foundation as analytics, plus reliable freshness and clear meaning. Change data capture into a governed platform is the usual route. Pointing an AI tool directly at a legacy database tends to create both performance and security problems. Getting the data AI-ready matters more than the connection itself.
• New applications that need to act on legacy data. An API layer is usually the right answer, because it lets new systems read and write through a controlled, documented interface instead of reaching into the old system directly.
• A one-time move to a new system. This is migration rather than integration. A temporary integration often runs alongside it so old and new systems stay in sync during the transition.

Should you integrate a legacy system or replace it?

Integrate when the legacy system still does its job reliably and the main problem is that its data and functions are hard to reach. Plan to replace it when it is unsupported, carries security vulnerabilities that cannot be fixed, depends on skills you can no longer find, or costs more to keep running than to rebuild.

The two are not opposites. A common path is to integrate first, with an API layer in front of the legacy system, and then replace its functions one by one behind that layer, a pattern often called the strangler fig. New applications talk to the API and never notice which system answers. The integration you build today becomes the route to retiring the system later, instead of another dependency that makes replacement harder.

Skills often decide the timing. In Kyndryl’s 2025 survey, 70% of organizations said they struggle to find people with the multi-skilled profile modernization needs. A system that only a few retiring engineers understand is a stronger case for replacement than one that is simply old.

What goes wrong in legacy system integration?

Legacy integration projects usually go wrong in the same few ways: undocumented systems, connections that multiply without a plan, security gaps, and data that moves correctly but means something different on each side. The technical connection is rarely the hardest part.

• Nobody knows exactly what the system does. Documentation is missing or out of date, and the people who built it have moved on. Mapping data and logic first, through a data discovery exercise, saves rework later.
• Point-to-point spaghetti. Each new project builds its own connection to the legacy system until nobody can change it without breaking something. A shared integration layer avoids this.
• Security added last. New connections create new credentials and service accounts, often with broad access to old systems that were never designed for it. The same risks covered in our guide to secure data pipelines apply.
• Same field, different meaning. Data arrives intact but means something different from the newer system’s version of the same field, and reports quietly disagree.
• Overloading the old system. Heavy queries from new tools can slow the legacy system down for the people who depend on it. Replication or caching protects it.
• Relying on screen automation for core flows. It works until the next interface change.

Infomineo transforms complex data into predictive insights and actionable intelligence through end-to-end analytics services, including data engineering and pipeline development and data quality assurance and validation. We leverage industry-leading tools and technologies, from Python and R to cloud platforms and machine learning frameworks.

Talk to our data analytics team →

Frequently Asked Questions

What is legacy system integration?

Legacy system integration connects an older system the business still relies on, such as a mainframe, an old ERP, or a long-running database, to newer applications, data platforms, or AI tools, so data and processes can flow between them without replacing the old system.

What is the difference between legacy integration and legacy modernization?

Integration keeps the legacy system and connects it to newer systems. Modernization changes or replaces the legacy system itself. Many organizations integrate first, often through an API layer, and then modernize the system gradually behind that layer.

Can AI tools connect directly to legacy systems?

They can, but it is rarely a good idea. Direct access can overload the old system and expose it to new security risks. Copying the data into a governed, modern data platform first is usually safer and gives the AI cleaner, better-documented data to work with.

How long does legacy system integration take?

It depends on the system and the approach. A scheduled export for reporting can be set up quickly. An API layer or real-time integration for a poorly documented core system can take months, mostly because of the time needed to understand the system and test the integration safely.

When should a legacy system be replaced instead of integrated?

When it is no longer supported by its vendor, has security vulnerabilities that cannot be fixed, depends on skills the organization can no longer find, or costs more to maintain than to rebuild. If it still works reliably and the main issue is access, integration is usually the better first step.