COBOL modernisation just got an AI shortcut–and the market noticed

It’s an open secret (that is, not many people seem to know) that the institutions keeping the global financial system turnig over run code that is ancient, barely understood, and frighteningly hard to replace. Now, AI is finally making that problem solvable – and the market has responded with a reality check for one of technology’s oldest names.

IBM shares recorded their worst single-day drop in more than 25 years earlier this week, plunging 13% after AI startup Anthropic said its Claude Code tool can accelerate COBOL modernisation – the kind of painstaking, expensive legacy work that has underpinned a portion of IBM’s consulting revenue for years.

An Anthropic blog stated that “modernising a COBOL system once required armies of consultants spending years mapping workflows,” and argued that tools like Claude Code can now automate the exploration and analysis phases that consume most of the effort in COBOL modernisation. That single claim was enough to send investors reaching for the sell button.

COBOL is bigger than most realise

To understand why the reaction was so sharp, it helps to understand just how entrenched COBOL remains. Hundreds of billions of lines of COBOL code run in production daily, powering critical systems in finance and government sectors. The language handles an estimated 95% of ATM transactions in the US alone.

The deeper problem isn’t the code itself – it’s the people who understand it. The number of developers who understand COBOL continues to shrink as the workforce that built these systems has largely retired. That talent scarcity is precisely what made COBOL modernisation so expensive for so long, and what made large consulting engagements – the kind IBM and rivals like Accenture and Cognizant built profitable practices around – essentially unavoidable.

Anthropic argues that AI flips this equation entirely. Claude Code works by mapping dependencies in thousands of lines of code, documenting workflows, identifying risks faster than human analysts, and providing teams with deep insights for informed decision-making. The company says teams can now modernise COBOL codebases in quarters not years.

IBM was already here

What the market’s reaction may be overlooking is that IBM itself has been making this argument for some time. Anthropic’s post comes about three years after IBM itself suggested using AI to rewrite COBOL as Java and created a product called “watsonx Code Assistant for Z” to do it. IBM CEO Arvind Krishna said as recently as July 2025 that the company’s AI coding assistant for mainframes “has got very adoption,” with the majority of customers using it to understand their COBOL codebase and decide what to modernise.

IBM defended its position on Monday, saying its mainframe platform delivers the same quality of performance and security regardless of programming language – COBOL or otherwise. And analysts were quick to add nuance to the panic.

Evercore ISI analyst Amit Daryanani noted that “clients already had the option to migrate from the mainframe, yet they are sticking with the platform,” suggesting the fear of displacement may be outrunning the reality.

The broader pattern

IBM wasn’t alone in taking a hit. Accenture and Cognizant also declined following the news – a sign that investors are looking at the entire consulting model around legacy modernisation, not IBM’s mainframe hardware business. Just last week, cybersecurity stocks sold off sharply after Anthropic announced Claude Code Security, a tool that scans codebases for vulnerabilities.

The pattern is becoming familiar: each new AI ability announcement triggers a reassessment of which existing revenue streams might be compressed, and the market prices in fear immediately.

IBM didn’t stay quiet. Rob Thomas, the company’s Senior Vice President and Chief Commercial Officer, pushed back directly in the aforementioned blog post, drawing a line the market appeared to have missed: “Translating code is one thing. Modernising a platform is something else entirely. The two are not the same, and the gap between them is where most enterprises run into trouble.”

His argument is worth sitting with. The value IBM’s mainframe delivers, Thomas contends, has nothing to do with COBOL as a language – it lives in the vertically integrated stack underneath it: z/OS, transaction processing architecture, quantum-safe encryption, and decades of hardware-software optimisation that no code translation tool touches.

Anthropic’s Claude Code, in his reading, is solving a real problem – just not the one that matters most for enterprises running IBM Z. He also raised a point that complicates the headline narrative further: roughly 40% of COBOL actually runs on Windows, Linux, and other distributed platforms – not mainframes at all.

Much of what’s being framed as an IBM mainframe story is partly a distributed systems problem that has been folded into a mainframe headline. IBM’s own clients are already making the case.

Royal Bank of Canada has used IBM’s watsonx Code Assistant for Z to map dependencies and build modernisation blueprints for core applications. The National Organisation for Social Insurance reported a 94% reduction in time to analyse legacy COBOL code using the same tool – cutting an eight-hour task to roughly 30 minutes.

Whether Monday’s selloff was a fair verdict or a reflexive one, the underlying change is real: AI is making COBOL modernisation economically viable for the first time in decades. The question IBM is asking – and the market hasn’t fully answered – is whether that’s a threat to its business or an acceleration of the transformation it’s already leading.

See also: Hitachi bets on industrial expertise to win the physical AI race

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