A Blog Post About COBOL Just Cost IBM $30 Billion. Here’s What Actually Happened.

DevOps.com

by Tom Smith

February 25, 2026

AI-Generated Deep Dive Summary

A single blog post from Anthropic caused IBM's market value to plummet by $30 billion, revealing how AI hype can drive market volatility rather than fundamentals. The post claimed that Anthropic's AI could modernize COBOL, a decades-old programming language widely used in enterprise systems, but this technology has been around for years and is not new. This incident highlights the risks of overhyping AI advancements and their potential impact on established industries. IBM has long relied on COBOL for critical business operations, with mainframes running much of the world's financial and transactional data. While modernization efforts have been ongoing for years, the blog post suggested that Anthropic's AI could revolutionize the process, spurring fears among investors about the obsolescence of traditional systems. This led to a significant drop in IBM's stock price, despite the fact that COBOL modernization has been a slow, incremental process rather than an overnight transformation. For those in DevOps and tech, this case underscores the importance of distinguishing between hype and reality when it comes to AI-driven innovations. The episode demonstrates how quickly markets can react to sensational claims about AI, even when the underlying technologies are not as groundbreaking or disruptive as they seem. It also raises questions about the long-term viability of COBOL and other legacy systems in an era of rapid technological change. Ultimately, this situation serves as a cautionary tale for professionals in DevOps and tech industries. While AI has the potential to drive significant advancements, it is crucial to approach claims with skepticism and focus on the practical implications rather than speculative hype. Understanding the true value of established technologies and their modernization processes can help mitigate risks and ensure more informed decision-making in an increasingly volatile market landscape.

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Originally published on DevOps.com on 2/25/2026