Shares of IBM recorded their sharpest single-day drop in more than 25 years on Monday after fresh concerns emerged over the impact of artificial intelligence on the company’s mainframe and services business.
The trigger came from AI startup Anthropic, which said its Claude Code tool is capable of understanding and modernising COBOL, a decades-old programming language that continues to underpin many mission-critical systems running on IBM’s mainframes.
IBM stock closed down 13.2% at $223.35, marking its biggest daily fall since October 18, 2000. According to Reuters, the sell-off has pushed the stock down roughly 25% so far this year, as investors reassess how quickly AI tools could reshape the economics of enterprise software and IT services.
Why COBOL Matters to IBM
COBOL, short for Common Business-Oriented Language, was created in the late 1950s and remains deeply embedded in global banking, insurance, airline systems, and government infrastructure. IBM has spent decades building and supporting mainframe systems optimized for large-scale transaction processing, where COBOL continues to play a central role.
Anthropic estimates that around 95% of ATM transactions in the United States still rely on COBOL-based systems, highlighting both the language’s scale and its continued relevance.
For years, modernising COBOL systems has required lengthy, consultant-led projects. These projects often involve teams manually tracing dependencies across vast codebases, documenting poorly understood workflows, and identifying integration risks. Such efforts have generated steady services revenue for companies including IBM.
What Anthropic Claims
In a recent blog post, Anthropic said its Claude Code tool can automate large parts of COBOL modernisation. According to the company, AI can analyse extensive codebases, trace dependencies across thousands of lines of code, generate documentation, and flag potential risks that would otherwise take months of manual effort to uncover.
“Hundreds of billions of lines of COBOL run in production every day,” Anthropic wrote. “Despite that, the number of people who understand it shrinks every year.”
The company argued that AI changes the cost equation. “Legacy code modernisation stalled for years because understanding legacy code costs more than rewriting it. AI flips that equation,” it said, adding that projects that once took years could now be completed in quarters.
These claims appear to have unsettled investors concerned that AI-driven automation could reduce demand for traditional consulting-heavy transformation projects.
Market Reaction and Broader Sentiment
The sharp fall in IBM shares reflects a broader shift in market sentiment toward enterprise software and IT services firms. Over recent weeks, investors have been weighing the speed at which AI tools are moving from experimental deployments to production use in large organisations.
Anthropic has also launched multiple Claude plug-ins designed to automate complex software tasks, positioning AI as an application layer capable of handling activities traditionally performed by consultants and integration teams.
The anxiety is not limited to the United States. Indian IT stocks have also faced pressure amid concerns that AI-led automation could reduce the need for large delivery teams.
However, industry views remain divided.
Hari Shetty, Chief Strategist and Technology Officer at Wipro, recently said that AI is more likely to expand opportunities for IT services firms than diminish them. He suggested that the range of potential AI-enabled services could create new areas of work.
By contrast, Vishal Sikka, former CEO of Infosys, has warned that generative AI is already changing how enterprise projects are executed. He noted that the disruption is tangible, particularly in areas such as code migration and system integration, where productivity gains are becoming evident.
What It Means for IBM
IBM’s business model has evolved in recent years to include hybrid cloud, AI, and consulting services alongside its traditional mainframe operations. However, the company’s installed base of mainframe customers and associated services revenue remains significant.
If AI tools meaningfully reduce the time and cost required to modernise legacy systems, it could alter pricing structures and margins in consulting-heavy projects. At the same time, AI adoption may also create new service opportunities, including AI integration, governance, and risk management.
For now, the market response indicates that investors are reassessing how quickly AI-driven automation could affect long-established revenue streams tied to legacy technologies.
IBM has not publicly indicated that its core mainframe strategy is changing. The longer-term impact will likely depend on how rapidly enterprises adopt AI-based modernisation tools and whether established firms can integrate such capabilities into their own service offerings.
