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IBM

2 Reasons IBM's COBOL Fears Are Overblown

March 26, 2026 — 09:07 am EDT

Written by

Anders Bylund for

The Motley Fool->

Key Points

- IBM shares dropped 13% on Feb. 23, on fears that Anthropic's Claude Code AI would accelerate COBOL modernization and undermine the mainframe business.

- AI can help translate legacy code, but it can't compress the testing, validation, and regulatory approval that migrations require.

- Big Blue's thriving mainframe business remains protected by institutional caution, not just technical complexity.

- 10 stocks we like better than International Business Machines ›

International Business Machines (NYSE: IBM) shares took a 13% nosedive on Feb. 23, their worst single-day drop in over 25 years. The culprit? Fears that Anthropic's Claude Code AI would make COBOL modernization so fast and cheap that IBM's mainframe cash cow would dry up practically overnight.

Just how different is COBOL?

For the curious, here's a simple "Hello World" program in COBOL:

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[hello.cbl]

000100 IDENTIFICATION DIVISION.

000200 PROGRAM-ID. HELLO.

000300 AUTHOR. JOE PROGRAMMER.

000400 ENVIRONMENT DIVISION.

000500 DATA DIVISION.

000600 PROCEDURE DIVISION.

000700 MAINLINE.

000800 DISPLAY 'Hello World!'.

000900 STOP RUN.

Compile, run, and enjoy the expected text message.

And here's the same thing in the modern Rust language:

fn main() {

println!("Hello, World!");

}

There are thousands of ways to do the same programming job, and they all generate the same output. An AI can translate between languages all day long.

But when that COBOL program is actually a 40-year-old payroll system with undocumented business logic and three people on Earth who understand it? That's a different story.

Here are two simple reasons IBM didn't have anything to fear from Claude's coding upgrades, even if the AI absolutely can do that job.

1. AI can read the code, but it can't magically erase the risk

Yes, Claude Code can apparently accelerate the "exploration and analysis" phase of COBOL modernization. That's genuinely useful. But here's the thing: Understanding old code was never the hardest part. After all, COBOL was designed to look and feel like simplified English, making it simple to maintain and fix over generations of different programmers.

The hard part is everything that comes after. Testing. Validation. Regulatory sign-offs. Change management committees. Convincing a room full of risk-averse executives that yes, we should absolutely touch the system that processes $3 trillion in daily transactions. These migrations usually only happen when the alternative is worse. Think Y2K, or end-of-life vendor support, or regulatory mandates with hard deadlines.

AI doesn't speed up institutional caution. Banks and government agencies aren't going to revamp their core infrastructure just because an AI can translate code faster than a human. That would be reckless.

2. Modernizing legacy systems is brutal, even when you know exactly what to do

I speak from experience here. Back in 2004, I was a Unix/Linux sysadmin tasked with upgrading a Sun-based Marimba/Castanet environment at a major railroad company. The existing installations were several versions beyond "unsupported" before I got the assignment.

I eventually made it work, but it took months of careful, step-by-step upgrades. And I was lucky enough to have a non-production clone to test on first. The stakes? If I messed up, the trains would stop, and the railroad didn't make money until somebody fixed it.

That was one company's internal operating software. Now imagine that same caution applied to COBOL systems running Social Security payments or interbank transfers -- or the Department of Defense's asset management. The code translation is the easy part. The deployment is where careers go to die.

Image source: The Motley Fool.

The big, blue bottom line

Big Blue's mainframe business isn't going away anytime soon. Hundreds of billions of lines of COBOL still run the world's most critical systems in crucial fields such as financial management and health records. The organizations that depend on them aren't going to rush migration just because the AI-based migration tools got better.

IBM's sell-off always looked like a buying opportunity, not a doomsday prophecy. It's still a solid buy a month later.

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