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The $5 Billion Problem Holding US Businesses Back

By Tui Leauanae
Sep 15, 2025

Summary

5 min
  • Legacy debt is now a business drag:
    Banks, hospitals, and agencies still run critical workloads on decades-old stacks like COBOL—raising risk, inflating run costs, and depending on a shrinking talent pool.

  • Modernize with security built in:
    AI is accelerating code analysis, conversion, and testing, while data protection—tokenization, format-preserving encryption, and masking—keeps sensitive data safe throughout the journey.

Much of the economy still runs on code written long before cloud or AI. That legacy debt shows up as mounting security exposure, escalating maintenance budgets, and a talent crunch for older languages. The market signals are clear: modernization spend is growing rapidly in the US and worldwide as leaders confront the cost of standing still.

Modernization is not one size fits all. Some teams rehost to the cloud to stop the bleeding; others refactor into services or rebuild to unlock speed and resilience. What’s different now is the multiplier from AI—tools that analyze and translate code, automate tests, and de-risk timelines that once spanned years. The other shift is philosophical: privacy-by-design is no longer optional. Protecting sensitive data with tokenization, format-preserving encryption, and dynamic masking lets organizations move faster without compromising compliance.

The takeaway for executives is simple: treat modernization as an investment, not overhead. Those who move decisively can redirect budget from upkeep to innovation, strengthen security, and prepare for AI-powered transformation. Those who don’t face rising costs, fragile systems, and dwindling expertise.