Rocket Software launches AI tools to accelerate IBM i modernisation
New AI-driven code analysis and unit testing aim to reduce the risk and manual effort of updating aging enterprise systems.
Rocket Software has introduced a suite of AI-driven tools specifically designed to assist organizations in the modernisation of IBM i systems. The initiative aims to help enterprises transition legacy workloads and improve operational efficiency by leveraging artificial intelligence to handle complex migration tasks.
According to confirmed reports, the new capabilities focus on two critical bottlenecks in the modernisation process: AI-based code analysis and AI-generated unit testing. By automating the evaluation of existing code and the creation of tests to verify its functionality, Rocket Software intends to streamline the process of updating legacy applications. While the primary focus is on IBM i, the company has extended these AI capabilities to include IBM Z, MultiValue, and Uniface environments.
The Legacy Challenge
IBM i, formerly known as the AS/400, remains a cornerstone of infrastructure for many large-scale enterprise environments. However, modernising these systems is traditionally viewed as a high-risk, high-complexity endeavor. This difficulty stems largely from the extreme age of the underlying code and a dwindling pool of skilled developers who possess the expertise to maintain or rewrite these proprietary systems without introducing critical failures.
Reducing Migration Risk
The integration of AI into the modernisation workflow significantly reduces the manual effort required to analyze and rewrite decades-old code. By utilizing AI for code analysis, developers can more quickly map dependencies and understand the logic of legacy systems. Furthermore, the introduction of AI-generated unit testing provides a safety net, ensuring that new versions of the software behave identically to the originals, thereby lowering the risk of operational downtime during digital transformation.
Future Outlook
As large enterprises continue to rely on IBM i infrastructure, the adoption of AI-assisted tools may accelerate the pace of cloud migration and application refreshes. Industry observers will be watching to see if these tools can effectively bridge the talent gap created by the scarcity of legacy developers. It remains to be seen how these AI tools will integrate with broader DevOps pipelines to provide a continuous modernisation path for the remaining IBM i install base.