The COBOL Conundrum: Why Modernization Has Been So Difficult

Developed in 1959, COBOL (Common Business-Oriented Language) was designed to be a universal, English-like language for business applications. However, its age has created a complex web of challenges. Modernizing COBOL isn’t simply a matter of translation; it’s a painstaking process hampered by poorly documented code, decades of accumulated institutional knowledge, and a dwindling pool of skilled programmers. Most computer science programs no longer include COBOL in their curriculum, exacerbating the shortage of qualified professionals.

The most significant hurdle, according to Anthropic, lies in the initial analysis phase – deciphering the intent and functionality of the existing code. This process is notoriously time-consuming and expensive. Claude Code aims to alleviate this bottleneck by automatically uncovering hidden workflows, identifying dependencies within the codebase, and providing engineers with actionable insights for redesigning systems.

“With , teams can modernize their COBOL code base in quarters instead of years,” Anthropic asserts in its recent blog post. Read more about Anthropic’s approach to COBOL modernization here.

IBM Pushes Back: The Complexity Beyond Translation

IBM, however, maintains that the analysis phase isn’t the primary obstacle. A spokesperson for the company stated, “Translating COBOL is the easy part—the real work is data architecture redesign, runtime replacement, transaction processing integrity, and hardware-accelerated performance built over decades of tight software and hardware coupling.” IBM argues that its decades of experience in optimizing these tightly integrated systems, coupled with the power of AI, positions it uniquely to address these challenges.

The company believes AI is a powerful tool, but emphasizes the depth of expertise required to navigate the complexities of mainframe modernization. Understanding the intricacies of COBOL is only the first step.

Did You Know?:

Government Reliance and Geopolitical Implications

Despite numerous modernization attempts, the U.S. government remains heavily reliant on COBOL-based mainframe systems for critical financial transactions, including Social Security benefits, tax processing, and Medicare reimbursements. The continued dependence on this legacy system raises concerns about security vulnerabilities and the ability to adapt to evolving technological demands.

Adding another layer of complexity, Anthropic is currently engaged in a separate dispute with the government regarding the safety guardrails on its AI models. CEO Dario Amodei is scheduled to meet with Defense Secretary Pete Hegseth to address concerns about providing AI for autonomous weapons systems or mass surveillance. Currently, Anthropic’s models are the only ones authorized for use with classified government information.

Anthropic insists that the timing of its COBOL modernization announcement is unrelated to this ongoing disagreement, characterizing it as part of a broader series of content focused on code modernization and Claude Code. The debate over AI safety and government use highlights the delicate balance between innovation and national security.

Pro Tip:

Beyond these specific events, broader market trends may also be contributing to IBM’s stock decline. Investor anxieties surrounding the pace of AI adoption and recent sell-offs in enterprise software stocks, coupled with uncertainty surrounding new global tariff announcements, are creating a volatile environment for tech companies.

What long-term effects will AI-driven COBOL modernization have on the mainframe industry? And how will governments balance the need for modernization with security concerns?

Frequently Asked Questions About COBOL Modernization

• What is COBOL and why is it still used?

  COBOL, or Common Business-Oriented Language, is a decades-old programming language still vital for core systems in finance, government, and airlines due to its reliability and the massive investment already made in it.

• How does Anthropic’s Claude Code help with COBOL modernization?

  Claude Code utilizes AI to analyze complex COBOL code, uncover hidden workflows, and identify dependencies, significantly reducing the time and cost associated with modernization projects.

• What is IBM’s response to Anthropic’s claims?

  IBM acknowledges the power of AI but emphasizes that COBOL modernization involves more than just code translation; it requires expertise in data architecture, runtime environments, and hardware optimization.

• Why is the U.S. government still reliant on COBOL systems?

  Despite modernization efforts, the U.S. government continues to rely on COBOL for critical financial transactions due to the complexity and cost of replacing these deeply embedded systems.

• What are the potential risks of modernizing COBOL systems?

  Modernizing COBOL systems carries risks such as introducing new bugs, disrupting critical processes, and requiring significant investment in new infrastructure and training.

• Could AI-driven COBOL modernization lead to job losses for COBOL programmers?

  While AI may automate some aspects of COBOL modernization, it’s more likely to shift the demand towards professionals who can work *with* AI to manage and oversee the process, rather than eliminate the need for skilled personnel entirely.