Modern life feels fast, connected and increasingly effortless. We move money with a tap, access medical records in moments, track deliveries in real time and interact with public services online rather than in person. Technology has become so embedded in everyday life that we rarely stop to think about what is making it all work.

Behind the scenes, however, much of this digital world is supported by technology that is far older than most people realize. Across banking, healthcare, energy, logistics and government, critical systems built decades ago are still doing the heavy lifting. They continue to work, but often under growing strain, and at a rising cost.

Gartner reports that up to 80 percent of enterprise IT budgets are consumed by maintaining existing systems rather than enabling innovation. In 2024, IT decision-makers spent an average of US$2.7 million simply upgrading legacy technology, with much of that investment directed at risk reduction rather than growth. For many leaders, this spending feels unavoidable, yet it rarely delivers the flexibility or efficiency they are seeking.

Today, organizations have better tools and clearer ways of working to address the problem. Generative AI is making modernization more practical, while a growing body of research points to leadership behaviors as the critical enabler of success.

The quiet foundations of the economy

Legacy technology includes mainframes, large monolithic applications and tightly connected systems that were designed long before cloud computing, mobile access or real-time data became standard. Many of these platforms were well-engineered and have proven remarkably reliable. Research suggests that some core banking and government systems are more than 30 years old and still support millions of daily transactions (McKinsey).

Over time, these systems have been adapted repeatedly to meet new regulations, customer expectations and operating models. Layers of change have created environments that are difficult to understand and even harder to evolve. Documentation is often incomplete, and critical knowledge sits with a shrinking pool of specialists.

Despite this complexity, these systems remain essential. They process payments, manage insurance claims, control energy networks, coordinate supply chains and store sensitive public data. According to the World Economic Forum, failures in core digital infrastructure increasingly pose not just organizational risk but systemic economic risk.

The hidden cost of delay

Keeping legacy systems running can feel like the safest option. Customers are served, revenue continues to flow and major disruption is avoided. Yet research consistently shows that this approach carries long-term consequences.

Organizations with high levels of technical debt experience slower time to market, higher operational costs and reduced ability to respond to change. Maintenance spend continues to rise, while innovation budgets shrink. Over time, inefficiency becomes embedded in everyday operations, making transformation even harder.

In a business environment defined by volatility and rapid change, standing still quietly becomes a strategic risk.

How generative AI changes the equation

Historically, modernizing core systems was slow, expensive and risky. Understanding complex codebases required scarce expertise and extensive manual effort. According to McKinsey, up to 70 percent of large-scale transformation programs failed to meet their objectives, often due to underestimating complexity and organizational impact.

Generative AI is beginning to change this equation. Large language models can analyze vast amounts of legacy code, documentation and system data at speed. They help teams understand how systems really work, identify dependencies and surface hidden risks. Gartner estimates that AI-assisted software engineering can improve developer productivity by 30 to 45 percent in complex environments.

Generative AI can also support refactoring, automate documentation, generate test cases and accelerate migration to modern architectures. Human oversight remains essential, but the reduction in effort and uncertainty is significant.

The benefits extend well beyond technology teams. As systems become more transparent, organizations can identify outdated processes and manual workarounds embedded over decades. Research from Accenture shows that process simplification enabled by modern platforms can reduce operational costs by 20 to 30 percent.

There are also workforce benefits. Reducing dependence on hard-to-find legacy skills lowers operational risk and improves resilience. Employees spend less time managing workarounds and more time creating value.

A moment for thoughtful leadership

The technology holding up modern life is no longer invisible. System outages, cyber incidents and service disruptions are increasingly public, and they directly affect trust, reputation and valuation.

For CEOs, the question is no longer whether legacy systems need attention but how to approach change in a way that is practical, human and sustainable. Generative AI makes modernization more achievable than ever before, but success depends on leadership behaviors that support clarity, discipline and empathy.

Reinventing foundational technology is not about chasing trends. It is about responsibly strengthening the systems that support organizations, economies and daily life and ensuring they are ready for the future.

Opinions expressed by The CEO Magazine contributors are their own.