Legacy applications that still run but no longer serve the business are becoming a strategic liability, and Tieto argues that AI is now the deciding factor in whether modernisation succeeds or stalls.
According to Tieto, many organisations depend on systems that function technically yet cannot keep pace with shifting market conditions, expanding integration demands and tougher security requirements. The consequence is slower development, rising costs and a diminished ability to respond to change.
Modernisation starts with visibility, and this is where AI delivers immediate value. Legacy estates typically hide years of undocumented functionality and business logic. Few people understand why the code behaves as it does, where critical dependencies sit, or what might break when changes land.
Tieto notes that AI-assisted tools can map dependencies, generate missing documentation and clarify overall architecture, giving organisations a realistic view of what to modernise, in what order, and at what risk.
The bigger shift, Tieto suggests, comes from agentic AI. Where traditional tooling analyses systems or proposes isolated changes, AI agents can execute broader tasks against a defined plan. Working through APIs, an agent can flag outdated libraries, recommend and implement upgrades, apply fixes across a codebase and generate tests to validate the work. Human expertise remains essential, with a human-in-the-loop model keeping people responsible for oversight and final decisions.
None of this works without strong engineering foundations. Before wider modernisation begins, organisations need robust testing, delivery pipelines, continuous integration and monitoring, otherwise every change risks breaking existing functionality. Tieto highlights that AI can generate unit and integration tests for legacy code, surface untested paths and prioritise the areas most exposed to a given change, cutting regression risk while accelerating delivery.
Cloud migration, often treated as the centrepiece of modernisation, is more than a technical lift. The right path depends on whether the goal is rapid migration, cost savings or an entirely new architecture. AI can assess dependencies, identify migration candidates, support infrastructure automation and optimise cost and capacity, proving especially useful when decomposing monoliths and right-sizing cloud environments.
Crucially, Tieto stresses that modernisation must reconnect with business needs. In legacy environments, business rules are buried in code, scattered across documents or locked in the heads of individual experts. Business analysts play a central role here, with AI able to extract requirements from documents and tickets, detect inconsistencies and link business rules back to code and processes.
The firm’s conclusion is that AI will not replace architects, developers or business analysts, but it makes modernisation faster, more transparent and easier to manage. The real value lies in uniting analysis, implementation, testing, cloud migration and business understanding into one continuous approach, turning modernisation from a technical project into a strategic advantage.
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