According to a survey of more than 400 top IT executives across industries in North America, three in four respondents say they still have disparate systems using traditional technologies and tools in their organizations. Furthermore, the survey finds that most executives report being in the planning or preliminary stages of modernization.

By By Angel Montesdeoca and Maja Vukovic, IBM Corporation

Maintaining these traditional, legacy technologies and tools, often referred to as “technical debt,” for too long can have serious consequences, such as stalled development projects, cybersecurity exposures and operational inefficiencies. In this age of generative AI (gen AI), the proliferation of unique business applications will only increase, and so will technical debt.

At the same time, gen AI has the potential to be part of the solution, enabling application modernization to become an evolving process. In the past, application modernization referred to updating legacy applications to a scalable cloud environment on a modern stack through automation.

Today, application modernization encompasses the evolution of an application throughout its lifecycle, including its code, data and user experiences. IBM is proud to announce our upcoming IBM watsonx™ Code Assistant for Enterprise Java Applications, anticipated to be generally available later this year.

This tool harnesses the power of gen AI and automation to support the end-to-end application lifecycle. It provides developers with capabilities to assist their workflows across the application lifecycle, from understanding and planning to transforming, validating and deploying their applications.

By using these capabilities, developers can streamline the entire application lifecycle, helping to ensure efficient and effective modernization at every stage:

1. Application assessment: Understand what an application does, the technical feasibility of modernization, and its potential return on investment. This helps leaders decide which applications to modernize more effectively.
2. Modernization planning: Generate plans for application modernization at the enterprise scale, building a strategy and approach to address up to thousands of applications. Dynamically reprioritize plans as the application environment changes, considering client constraints and application dependencies.
3. Application transformation: Automate the transformation of applications by scoping out parts to modernize. For selected components, extract the code, business functions and business rules for transformation, with gen AI assistance to facilitate developers’ application modernization efforts.
4. Application testing: Automate test generation at different levels: unit, module and integration.
5. Automated deployment: Generate CI/CD pipelines that are context-aware.

Application modernization is not a one-time process. IBM watsonx Code Assistant for Enterprise Java Applications is engineered to support businesses adopt this continual approach to application modernization assisting with upgrading Java versions, regardless of runtime, and creating new Java applications. Available as a technology preview in June, IBM watsonx Code Assistant for Enterprise Java Applications is anticipated to be generally available later this year. Sign up for the waitlist.