IBM, watch out! Fujitsu uses AI to understand COBOL and automatically generate… is attracting attention across the tech world. Analysts, enthusiasts, and industry observers are watching closely to see how this story develops.
This update adds another signal to a fast-moving sector where product decisions, platform changes, and competition can quickly shape the market.
Fujitsu Application Transform cracks COBOL in no time at all
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Fujitsu has introduced a new generative AI service which analyzes COBOL and other legacy source code, automatically producing design documents in minutes rather than hours.
The platform can operate and automatically produce design documents without expert knowledge, reducing reliance on specialized human programmers.
The company says Fujitsu Application Transform powered by Fujitsu Kozuchi eliminates the need for extensive manual review, cutting the time required to understand complex source code by approximately 97%.
The service aims to provide a clear understanding of existing platform specifications, offering organizations a practical tool to support modernization strategies efficiently.
Compared with analysis conducted solely by general generative AI tools, Fujitsu’s proprietary solution enhances the quality of generated documentation.
This platform links large volumes of source code through a Knowledge Graph — Enhanced retrieval platform.
With this, it prevents omissions and hallucinations, ensuring the generated design documents reflect all relevant platform details.
This approach improves comprehensiveness by 95% and boosts readability by 60%, producing documentation that is easier for teams to interpret and act upon.
These improvements are particularly critical when dealing with COBOL, a programming language designed by Dr. Grace Hopper in 1959 that has an estimated 850 billion lines of code.
Although over 65 years old, COBOL remains widely used, and businesses remain heavily reliant on this venerable programming platform.
It often powers the core transaction platforms of banks, insurers, and government agencies without public visibility.
During the pandemic, the United States raised the prospect of a shortage of COBOL programmers to help manage critical platforms, showing its importance.
Before the Fujitsu platform, Anthropic noted that AI could help keep COBOL running for a long time.
Fujitsu plans to provide support services to guide organizations in deploying the platform effectively – this year, the company intends to introduce features for rebuilding existing source code for future use.
The platform will automatically rewrite code and support ongoing operation and maintenance.
This sequential advancement ensures that companies can not only understand legacy platforms but also adapt and maintain them with minimal manual intervention.
“We see this announcement as an initiative that realistically advances the modernization of our legacy platforms… we have come to recognize the potential of this tech innovation,” said Toshihiro Horiuchi, Managing Executive Officer, SMBC Nikko Securities Inc.
For many engineering teams, this announcement represents a clear advantage, but IBM, a major vendor of COBOL-powered mainframes and enterprise platforms, needs to revise its strategy or risk being outpaced in automated legacy platform modernization.
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Efosa has been writing about tech innovation for over 7 years, initially driven by curiosity but now fueled by a strong passion for the field. He holds both a Master’s and a PhD in sciences, which provided him with a solid foundation in analytical thinking.
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Why This Matters
This development may influence user expectations, future product strategy, and the competitive balance inside the broader technology industry.
Companies in adjacent segments often react quickly to similar moves, which is why stories like this tend to matter beyond a single announcement.
Looking Ahead
The full impact will become clearer over time, but the story already highlights how quickly the modern tech landscape can evolve.
Observers will continue tracking the next steps and how they affect products, users, and the wider market.
