IBM Watsonx Modernizes Mainframes with Generative AI

Next month, IBM watsonx Code Assistant for Z will make its debut. It’s the company’s new generative AI-assisted solution that it’s building to help enable faster translation of COBOL to Java on IBM Z. It aims to help accelerate and mitigate the risk of modernizing COBOL applications. The company will show off the solution at IBM TechXchange event in Las Vegas, Sept. 11-13.

New research from the IBM Institute for Business Value says organizations are 12 times more likely to leverage existing mainframe assets rather than rebuild their application estates from scratch in the next two years. At the same time, however, the study shows that the No. 1 challenge for those same organizations is a lack of resources and skills.

IBM says one major attribute of the code assistant is that it’s powered by the watsonx.ai code model, which will become one of the largest generative AI foundation models for automating code. At scale, using the code assistant compared to other approaches could make it easier for developers to selectively and incrementally transform COBOL business services into well architected high-quality Java code — with estimated billions of lines of COBOL code as candidates for modernization over time. Generative AI can help developers to more quickly assess, update, validate and test the right code, allowing them to more efficiently modernize large applications and focus on high impact tasks, IBM said.

IBM’s Kareem Yusuf

Kareem Yusuf, senior vice president, product management and growth at IBM Software, said bringing generative AI capabilities through watsonx to new use cases will drive progress for the company’s clients.

“IBM is engineering watsonx Code Assistant for Z to take a targeted and optimized approach. It’s built to mitigate the risk of modernization while converting code optimized for IBM Z, accelerating time to market and broadening the skills pool. This is designed to help enhance applications and add new capabilities while preserving the performance, resiliency and security inherent in IBM Z,” Yusuf said.

IBM Watsonx: Protecting Sensitive Data

A recent Gartner report says that “by 2028, the combination of humans and AI assistants working in tandem could reduce the time to complete coding tasks by 30%.” The report further states that “the use of AI code generation tools is not replacing the quality assurance (QA) processes and security controls that are needed by developers for robust and secure product development, as well as for mitigation of inherited risks from using generative methods for code.”

Protecting sensitive data and customer intellectual property are critical when it comes to implementing generative AI. For decades, the company has followed core principles, grounded in commitments to trust and transparency, IBM said. With this principle-based approach, the watsonx platform aims to enable enterprises to leverage their own trusted data and IP to build tailored AI solutions that are scalable across operations.