Technical debt is a growing challenge for organizations across all industries, with outdated and complicated systems negatively impacting business agility and innovation. Legacy applications often suffer from technical debt from unplanned updates and quick fixes to meet new business requirements. This makes it crucial to address technical debt through application modernization efforts.

Traditional and generative AI can both play a significant role in tackling this technical debt by optimizing legacy system performance, automating manual tasks, and enhancing various aspects of the modernization process. This can accelerate and reduce the overall cost of planning and executing many application modernization projects.

Read on to learn how AI can be used to facilitate modernization processes and be added to existing legacy applications to modernize them.

Modernizing Legacy Applications with AI

Legacy applications often suffer from outdated architectures, high maintenance costs, limited scalability, and many other issues. AI can assist in modernizing these applications by optimizing their performance and simplifying their source code.

AI algorithms can analyze system behaviors and identify bottlenecks that hinder scalability and reliability. By uncovering opportunities to boost performance and identifying potential fixes for critical bugs, AI can extend the lifespan of these legacy applications until workloads and processes can be fully transitioned to modern technologies.

AI can also help developers simplify complex legacy code to make it easier to understand and maintain older applications. For example, an AI algorithm can automatically refactor source code to make it more readable and aligned with certain coding standards and best practices. AI can also help generate comprehensive and up-to-date documentation for legacy applications, which can further facilitate future maintenance efforts.

Enhancing Application Modernization Processes Using AI

Besides being useful for optimizing legacy applications themselves, AI can also improve many modernization processes — from discovery and planning to testing and writing new code. In fact, AI can augment human intelligence to accelerate and reduce the cost of modernization initiatives.

When organizations decide to modernize a legacy application, they first need to discover what they’re dealing with. Many older systems lack detailed documentation and those tasked with supporting legacy applications may not have a complete understanding of how they work. AI-powered code analysis and reverse engineering can provide insights into the structure of legacy applications and help software teams map legacy code to business capabilities so that they can plan a new modernization project.

Generative AI can also automate tasks related to quality assurance. For example, automatically generating regression tests can help software teams make sure a modernized application meets the same functionality requirements as a legacy system. AI-powered automated testing can significantly accelerate quality assurance processes — including test creation, maintenance, and execution — to reduce existing technical debt and deliver modernized applications faster.

Finally, a less common but growing use case for generative AI in the modernization process is directly writing code. Code generation tools like GitHub Copilot are in their early stages of adoption, so they’re still generally limited to offering developers AI-generated recommendations rather than writing large amounts of code from scratch. However, one promising use case is automatically rewriting legacy code from an older language like COBOL or Perl over to more modern languages that are easier to manage.

AI for Application Modernization

As you can see, leveraging AI is a great way to modernize legacy applications as well as streamline the modernization process itself. AI-powered tools can analyze legacy codebases, identify areas for optimization, and automate tasks like code refactoring and testing. By leveraging AI, organizations can accelerate the modernization process, reduce costs, and improve the overall quality of their IT systems.

AI is also a great way to overcome the software skills gap when launching an application modernization initiative. Many organizations struggle to find and hire experts for the legacy technologies they rely on, which makes it difficult to maintain or update older applications. The ability for generative AI to work with legacy languages and poorly documented codebases can help development teams expand their capabilities to handle these modernization projects.

If you’re ready to adopt AI for your application modernization projects, consider partnering with AHEAD. We’re an enterprise technology expert that provides transformation services, including application and infrastructure modernization services to deliver solutions that are more reliable, resilient, and secure.

Our diverse teams of software and AI experts ensure you have access to all the technical talent necessary to successfully deliver modern digital platforms. We can also help jumpstart your AI journey by helping to integrate AI solutions into your existing applications, infrastructure, and workflows.

Contact us to learn more about our transformation services to design, build, and implement modern enterprise solutions.