Versions :<123456Live>
Snapshot 4:Tue, Feb 24, 2026 4:50:48 PM GMT last edited by Mr Bot

IBM Plunges 13% as Anthropic AI Tool Threatens COBOL Business

IBM Plunges 13% as Anthropic AI Tool Threatens COBOL Business

Image credit: 

The Spin

Generic AI models fail spectacularly at COBOL because they can't handle the unique structure, decades of embedded business logic and zero-tolerance error requirements that real migrations demand. Off-the-shelf tools like Opus 4.6 simply won't cut it for this specialized work. The market's panic over a single blog post completely ignores the actual technical reality that domain-specific training is absolutely essential for competent COBOL engineering.

Moving massive volumes of sensitive mainframe data to the cloud for AI processing creates unacceptable latency and security risks that make the whole approach impractical. Data gravity and the need for real-time transaction processing mean AI must come to the mainframe, not the other way around. The platform has evolved into an AI-optimized hub with integrated accelerators that can run complex neural networks alongside mission-critical workloads.


The Controversies



Go Deeper


Articles on this story



© 2026 Improve the News Foundation. All rights reserved.Version 6.18.0

© 2026 Improve the News Foundation.

All rights reserved.

Version 6.18.0