It’s 2025, and most enterprise technology leaders aren’t building the future—they’re managing the past. Despite years of digital ambition and billions in modernization budgets, the hard truth remains: technical debt has become the single biggest barrier to innovation, agility, and growth. HFS estimates the Global 2000 are carrying $1.5–2 trillion in accumulated tech debt.
This isn’t just a technology issue—it’s a structural trap. And much of the $1.5 trillion IT services industry is designed to keep enterprises in it.
For decades, organizations have turned to outsourcing, staff augmentation, and piecemeal automation to cope. But these legacy approaches have too often become part of the problem. They are incentivized to sustain complexity rather than eliminate it, resulting in normalizing stagnation with armies of offshore workers.
Now, AI presents a real escape route—not by making legacy cheaper to run, but by giving enterprises the tools to tear it down. AI can read and rewrite legacy code, automate integration and testing, and compress years of technical debt remediation into weeks.
But here’s the paradox: most organizations are still treating AI like just another tool—when it needs to be treated like a jackhammer.
This study, based on insights from more than 600 IT and business leaders across industries, reveals a growing recognition that breaking free from tech debt requires more than new technology. It demands a shift in mindset, delivery models, partner expectations, and operating architecture.
Enterprises are ready to act:
These aren’t signs of incremental change—they’re signals of a systemic shift. And they point to a new era in which outcome-aligned, AI-native delivery models will define competitive advantage.
This HFS Market Impact paper unpacks what that shift looks like—and outlines five bold moves CIOs must make to escape the trap of tech debt and build for what’s next.
If AI is the jackhammer, leadership is the ignition. The question is no longer whether to modernize—it’s whether you’re ready to break through.
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