AI-enhanced system modernization brings speed and cost efficiency

A year ago, revamping a large, customised enterprise resource planning system meant an investment easily running into six figures. Now, projects of a similar scale can be implemented with AI assistance at a fraction of the previous cost. The change applies not only to new systems, but also to the modernisation of existing ones.

Many companies’ key systems have served them faithfully for years and are critical to their business. However, the technical foundation and development practices of these systems reflect a time when there were no requirements for automation, analytics and artificial intelligence as we know them today.

This applies to many technologies that are still widely used, such as Java, .NET, Visual Basic, Perl and PHP-based solutions. Although these systems currently run the company’s most important functions, the challenge arises from the fact that their development, maintenance and utilisation in business changes are becoming more difficult year by year, costs are rising and the pace of development is slowing down.

Artificial intelligence brings new opportunities to system reform and modernisation, particularly in terms of visibility, speed and cost-effectiveness.

Why do legacy systems need to be developed?

Technological development does not stand still; over the years, the surrounding ecosystem changes. In systems that have been in use for a long time, development challenges often begin to appear within the system before they become visible externally. One key factor is expertise: the functioning of the system and its solutions often rely on the tacit knowledge of a small group of people. When understanding is not widely shared, development work slows down and risks increase.

Over the years, technical debt also accumulates in systems as a result of incremental solutions and changing requirements. This manifests itself in overlapping logic, entities that are difficult to test, and extensive areas of impact even with minor changes. At the same time, the libraries and components used in the background of the system may not receive up-to-date security updates, which weakens the overall security level and increases vulnerabilities without being noticed.

Structural solutions and inadequate documentation reinforce this phenomenon. When the system’s operation is based on tacit knowledge, adding new features requires more and more research, and the effects of changes are difficult to predict. These factors together increase manual work, lengthen development times and directly translate into higher costs, especially when the system does not support modern development practices.

Progress towards controlled modernisation

Once development needs have been identified, the next question concerns progress. Attention shifts from individual challenges to overall management: how can the system be developed so that changes are predictable, their effects understandable, and development work also supports future needs? At this stage, decision-making focuses primarily on the development model and the means by which the system structure and development work will be systematically advanced.

Artificial intelligence provides visibility into the actual operation of the system

The greatest risks of system reform arise in situations where decisions are made on the basis of incomplete visibility. Monolithic structures, poor documentation and far-reaching dependencies make it difficult to grasp the big picture.

Artificial intelligence can be utilised:

• structural analysis of the code base
• mapping dependencies and interfaces
• identifying critical components
• analysis of performance and usage priorities.

Artificial intelligence enables the system to be examined as a whole without months of manual investigation. The result is a technical overview that can be used as a basis for making well-founded architectural decisions.

Artificial intelligence supporting development work

Artificial intelligence is increasingly becoming part of actual software development. Existing code can be read, clarified and documented using artificial intelligence, which speeds up understanding and reduces manual investigation work. In practice, this means:

• faster understanding of existing code
• producing proposals for structural improvements
• supporting and supplementing documentation
• creation of test cases and interface descriptions

The most significant benefit is the predictability of development work. When the code base is better understood, the effects of changes are clearer and development time is reduced.

Code modernization and technology transitions

Another significant change is that old code can be modernised in stages with the help of artificial intelligence. Business logic can be transferred to new languages and architectures more cost-effectively than in traditional renewal projects. This makes modernization a realistic option even when a complete rebuild is not a sensible alternative.

AI-powered development enables:

• analysis of existing business logic
• translating code step by step into new languages and frameworks
• breaking down architecture into a more modular form

This enables controlled technology transitions without complete reconstruction. The transition can be implemented one component at a time, while maintaining stability in production use.

Read also: How can you get more out of Odoo ERP with AI?

Controlled modernization without service interruptions

Modernizing a system does not automatically mean a complete overhaul. Often, the most sensible approach is gradual development, where the old and the new coexist.

At Hurja, we plan modernization in such a way that the core of the system remains operational while new functionalities are built using modern technologies. Interfaces can be renewed, performance improved and the whole system clarified step by step.

Artificial intelligence helps identify dependencies and risk areas, allowing the reform to be scheduled and scaled correctly. This ensures that business operations continue uninterrupted and the investment can be divided into several manageable phases.

Cost benefits arise from management and allocation

When system reform is carried out using artificial intelligence, the cost benefits do not arise from a single action, but from the combined effect of several factors. The amount of investigative work is reduced when the current situation is understood more quickly. Manual work is reduced when processes are streamlined. Development work is accelerated when the system is clearer and better documented.

The end result is a system that costs less to maintain, is easier to modify, and supports business growth without a constant backlog of repairs. At the same time, the technical debt accumulated in the system becomes a manageable part of the whole. When structures, dependencies, and areas of influence are better understood, technical debt does not drive development unnoticed, but its effects can be consciously taken into account as part of planning and prioritisation.

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System modernization as part of business development

System modernization enhanced with AI is part of modern business development, aiming to create smoother daily operations, better predictability, and improved cost efficiency. The goal is to build a system that supports the next stage of business growth: faster decision-making, better use of data, and the ability to introduce new ways of working without excessive development effort.

We help our clients understand the current state of their systems, choose the right development path, and carry out modernization in a controlled and efficient way. The result is not only a technically improved system but also a solution that supports the business well into the future.