Kresimir Mudrovcic and his team of programmers spend months on end trawling through computer code that can be three times as old as the crew’s youngest members.
Mudrovcic specializes in mainframe technology, involving computers tracing their roots to the dawn of the digital age and the ancient software that sometimes runs on them. Upgrading such systems is painstaking work, often entailing sifting through millions of lines of code to understand how specific functions operate. Mudrovcic, an IT consultant, compares it to archeology.
But the work is getting easier, thanks to the widening use of generative artificial intelligence to do some of the heavy lifting. “AI systems work like that smart, very experienced, very wise old colleague who knows everything,” said Mudrovcic, whose team recently deployed such tools to help speed up modernizing the pension system of a European government agency.
Similar efforts are underway at companies and governments around the world, as the urgency to address aging computer code increases. The US Social Security Administration plans to use AI to help upgrade its legacy Common Business-Oriented Language code base, and expects the project to take three years and cost about $1 billion, a person with knowledge of the matter said.
The SSA didn’t respond to requests for comment.
From online banking applications and airline ticketing services to pensions disbursements, critical systems are often undergirded by decades-old code, raising costs as well as the risk of failures and cyberattacks. US Treasury Secretary Scott Bessent has repeatedly stressed the need to overhaul government systems running on computer language like COBOL, which was invented in the late 1950s.
“When I started in college in 1980, I learned to program in COBOL,” he told Bloomberg’s Big Take DC podcast in February.
As much as 70% of software used by Fortune 500 companies was developed at least two decades ago, according to a December report from McKinsey. Global financial institutions alone are expected to spend some $57 billion maintaining legacy payments systems in 2028, research firm IDC estimates. That’s almost equivalent to last year’s net income at JPMorgan & Chase Co., the biggest US bank.
“You’d be surprised how many firms are still on COBOL, even banks globally,” said Gokhan Sari, a senior partner at McKinsey. The consultancy has developed a dedicated AI tool called LegacyX to help clients including banks remove obsolete code and revamp their systems.
Until Sam Altman’s OpenAI ushered in the generative AI frenzy with ChatGPT in late 2022, managing systems based on dated languages like COBOL and PL/1 meant tapping into a dwindling pool of talent as experienced programmers versed in such code retired. It wasn’t unheard of for companies to call former employees back from retirement when a system needed maintenance.
