AI Tools Disrupt COBOL Modernisation Market, Affect IBM and Consultancies
AI startup Anthropic's launch of Claude Code, an AI tool that accelerates COBOL system modernisation, triggered a sharp drop in IBM shares and broader consulting sector declines. The development highlights how AI may disrupt revenue streams built around legacy code maintenance, prompting market reassessment of the consulting model. While IBM has its own AI solutions for COBOL, the speed, scope, and pricing of modernisation are now under scrutiny.
Artificial intelligence is reshaping the landscape of legacy system modernisation, with new tools capable of automating and accelerating the transformation of COBOL, one of the world’s oldest programming languages. This week, the market responded sharply to the debut of Anthropic's Claude Code tool, which claims to dramatically reduce the cost and complexity of COBOL system upgrades.
IBM shares experienced their steepest single-day decline in over 25 years, dropping 13% following Anthropic’s announcement. Claude Code is positioned as an AI-powered assistant for code exploration and workflow mapping—a significant portion of the human labour involved in COBOL modernisation. For decades, consulting giants like IBM, Accenture, and Cognizant have relied on high-margin services to replace or upgrade critical COBOL infrastructure, especially within the financial and public sectors.
COBOL (Common Business-Oriented Language) remains deeply embedded in global financial systems. Industry estimates suggest hundreds of billions of lines of COBOL run daily, powering banking, government, and transaction processing systems—including roughly 95% of ATM transactions in the United States. The ongoing challenge has been the scarcity of developers fluent in COBOL, as many experts have retired, making code modernisation projects time-consuming and costly.
Anthropic argues that its Claude Code tool uses AI to automate analysis of vast codebases, map dependencies, document complex workflows, and identify risks faster than manual review. According to Anthropic, modernisation tasks that required years of consulting work can now be completed in months, shifting the economics of legacy technology upgrades.
However, some analysts and industry players caution against conflating code translation with true platform modernisation. IBM, which has marketed its own AI-powered COBOL tools such as watsonx Code Assistant for Z, contends that the critical value of its mainframe offering lies in the integrated hardware-software stack and its performance, security, and reliability. Rob Thomas, IBM’s Senior Vice President and Chief Commercial Officer, emphasised in a company blog that translating code does not address the broader challenges of modernising complex enterprise systems.
Market analysts noted that client migration away from mainframes has long been an option, yet many financial institutions continue to rely on them. The rapid market sell-off affected not only IBM but also other consulting-dependent firms, suggesting investor concern about the sustainability of the entire modernisation services model amid accelerating AI advances.
Recent client reports show that AI-assisted tools can deliver major efficiency gains. For example, the Royal Bank of Canada used IBM’s AI tools to map dependencies and design modernisation plans, while the National Organisation for Social Insurance reported a 94% reduction in analysis time for legacy COBOL code.
Despite investor concerns, the core question remains whether AI-powered modernisation presents a fundamental threat to incumbent technology providers or accelerates transformations already underway. The impact on consulting revenue, mainframe adoption, and the role of AI in enterprise architecture will become clearer as more organisations deploy these new tools.
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