The systems used by essential federal agencies, such as the Department of Health and Human Services, the Social Security Administration and the Centers for Medicare and Medicaid Services, still run critical systems on outdated languages like COBOL, and the urgency to refactor and upgrade extends beyond rising costs.
Legacy systems represent an expanding attack surface with diminishing defensive capabilities. With each passing year, the risk of catastrophic system failures that could interrupt benefit payments, compromise sensitive information, or create processing backlogs affecting millions of citizens increases.
Many agencies have postponed comprehensive modernization efforts, opting instead to maintain legacy systems and address vulnerabilities as they emerge. This approach has resulted in technical debt that multiplies like compound interest.
As agencies face increasing pressure to enhance efficiency, the public sector has an opportunity to enter the AI era with a critical use case: modernization. I previously wrote about the importance of modernizing legacy applications with memory-safe code and how agencies can leverage AI to accelerate what was once an unwieldy, time-intensive process.
Now is the time to put modernization initiatives into motion. AI-powered modernization tools can transform what was once a years-long endeavor into an accelerated path for agencies to retire their COBOL and legacy language dependencies.
The basics of code refactoring
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