The first step businesses can take to move legacy systems to agentic AI

For decades, most large enterprises have carried at least one system too vital to switch off and too fragile to change - its rules were written long ago, never fully documented, and only understood by a shrinking few. It fails security reviews, drains budget to keep alive, and now stands directly in the way of AI; agents and models can't run on a closed, undocumented system with no clean data or APIs. Modernising it used to mean a multi-year, high-risk programme most boards deferred.

Two things have changed - AI has made the rebuild fast and safe to attempt, and legacy has become the single biggest blocker to AI ambitions. 85% of senior executives are concerned their existing technology estate will imperil their ability to adopt AI. Modernisation is no longer overdue maintenance; it is now the first step to agentic AI.

“For the first time, the systems enterprises we were often afraid to touch are the ones that can now be modernised with confidence,” said Ciarán Cosgrave, CEO, Nearform. “AI is both the reason to modernise and the means to do it - it's not a project you run alongside your AI strategy, it's what unlocks it.”

At the core is Nearform's Agentic Modernisation Engine - a pipeline of specialist AI agents, with a parity harness that continuously tests the rebuilt system against the original to prove it behaves identically. Through it, Nearform helps clients:

• recover the business logic buried in legacy code as documented, plain-language specifications;
• section the port into sensible chunks, enabling both humans and models to keep pace with the context of what has changed
• rebuild it on a modern stack of the client's choosing - the original language no longer dictates the future;
• prove behavioural parity against live data before go-live, avoiding a single high-risk cutover; and
• retain full ownership — documentation, tooling and knowledge handed back, with no lock-in.

Building an AI-ready foundation means you get more than a system that solely runs. The business logic once trapped in legacy code becomes living documentation, test suites and governed services. And, as it has been cast from the shackles of a legacy technology stack, capabilities like MCP can be added to once legacy servers, enabling the interoperability of both old workloads and agentic ones together.

Nearform specialises in modernising complex legacy estates wherever they exist, whether in mainframe and COBOL environments or decades-old applications built with ASP.NET, VB6, PHP, and SQL. By unlocking the business logic embedded across these systems, organisations can reduce risk, improve interoperability and create a foundation for AI-driven capabilities.

For many organisations, this work is not just about innovation but risk reduction. Years of technical debt have left critical business systems running on ageing platforms with security vulnerabilities that are increasingly difficult to identify, remediate and govern. Modernisation therefore becomes a prerequisite for AI adoption, improving security, reducing exposure to emerging threats and creating a foundation that can safely support both current operations and future AI-driven capabilities.

Importantly, while AI does the heavy lifting, judgement remains firmly human. Nearform embeds senior engineers directly within client teams, delivering into production environments where context, experience and decision-making matter most. As AI increasingly takes on execution, the greatest value comes from understanding business requirements, managing risk and making the right architectural choices.

“AI tackles a level of scale never before possible; our senior engineers and the client's own experts make the judgement calls to ensure a smooth modernisation journey,” said Cian Clarke, Head of AI.

This approach allows organisations to validate outcomes before committing to large-scale transformation programmes. For one major insurer, the replacement of a thirty-year-old, 1.5-million-line platform had been repeatedly deferred because the perceived risk was simply too high.

In a three-week proof of concept, Nearform catalogued 269 forms and 1,259 complexity points in a matter of hours, rebuilt working software that achieved parity against live production data without requiring data migration, and produced a roadmap for a phased ten-to-twelve-month delivery programme. Throughout the process, the existing platform remained live and untouched, demonstrating that modernisation no longer has to begin with a high-risk leap of faith.

For years, legacy modernisation was viewed as a costly, high-risk undertaking that could be postponed until a more pressing need emerged. That moment has now arrived. As organisations race to deploy AI, the systems that underpin critical business processes have moved from being technical debt to becoming strategic constraints.

Agentic systems require accessible services, interoperable architectures and trusted foundations, none of which can be built on opaque, undocumented platforms designed for a different era. By combining AI-driven reconstruction with behavioural parity testing and senior engineering expertise, Nearform offers organisations a path to modernise with confidence rather than compromise. The result means a migrated application, that is secure, governed and holds an AI-ready foundation capable of supporting both today's operations and tomorrow's autonomous workflows.

In the AI era, modernisation is no longer the destination. It is the starting point.