The future belongs to organizations that treat modernization as an ongoing discipline, not a one-time initiative.
As organizations accelerate modernization efforts and explore new opportunities with artificial intelligence (AI), many are facing a common challenge: managing increasingly complex IT environments.
Decades of technology investments have enabled businesses to grow, adapt, and innovate. Applications have evolved to meet changing business needs. New systems have been integrated through acquisitions. Cloud services now work alongside mission-critical mainframe workloads. Over time, that evolution has created environments that are far more interconnected than many organizations realize.
For enterprises running business-critical mainframe environments, technical debt has become more than an IT concern. It influences operational resilience, business agility, investment decisions, and an organization’s ability to modernize with confidence.
Industry estimates suggest that technical debt costs enterprises $2.41 Trillion annually, with $1.52 Trillion needed to remediate it. But beyond the financial impact, the bigger challenge is that it makes it harder to respond to changing business demands while continuing to deliver the reliability organizations depend on.
“Technical debt costs enterprises $2.41 Trillion annually, with an estimated $1.52 Trillion needed to remediate it.”
Although the goal isn’t to eliminate technical debt altogether. Every organization accumulates some level of it as technology and business requirements evolve. It’s understanding where technical debt creates the greatest business impact, so modernization efforts can be focused where they’ll deliver the most value.
Why Visibility is the First Step
One of the questions I hear most often from IT leaders is, “Where do we start?” My answer is usually the same: start by understanding your environment.
Enterprise systems have been evolving for decades. Business-critical applications have been enhanced countless times. New integrations have been added. Infrastructure has expanded. In many organizations, documentation simply hasn’t kept pace with years of change.
I’ve seen customers delay modernization efforts—not because the technology couldn’t evolve, but because they lacked a clear understanding of application dependencies, runtime behavior, or the downstream impact of changes.
Without that visibility, modernization becomes much harder than it needs to be.
Before making modernization decisions, I always encourage customers to create a comprehensive view of:
- Application dependencies
- Operational workflows
- Infrastructure relationships
- Runtime behavior
Understanding how those pieces fit together makes it much easier to identify where complexity has accumulated and where modernization efforts will have the greatest business impact.
Fortunately, today’s analysis tools make that process far more practical than it was just a few years ago. For one, automated discovery can uncover hidden dependencies, duplicated logic, and other sources of technical debt across large application portfolios.
Additionally, AI can help teams interpret insights more quickly, giving them the context they need to make informed decisions without relying solely on documentation or institutional knowledge. We’re seeing customers explore conversational AI assistants, such as Rocket EVA, to interact directly with their mainframe — helping them better understand complex application environments and make more informed modernization decisions.
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Which Technical Debts Actually Matter
One misconception I often encounter is the assumption that older systems automatically represent technical debt. That’s rarely true.
I’ve worked with customers whose COBOL applications have reliably supported critical business processes for decades with very little intervention. At the same time, I’ve seen much newer applications become expensive to maintain due to undocumented dependencies, inefficient workloads, or growing operational complexity.
“There is a misconception that older systems automatically represent technical debt. That’s rarely true.”
Instead of looking at applications in isolation, I encourage customers to focus less on what an application is and more on what it’s doing for the business. Once you shift that perspective, four key questions emerge:
- Which workloads consume disproportionate CPU resources?
- Where are the biggest operational bottlenecks?
- Where are maintenance costs increasing without delivering additional business value?
- Which systems make it harder to respond to new customer expectations or regulatory requirements?
Answering these questions helps separate the systems that continue to deliver value from those that create unnecessary complexity.
Performance data plays an important role by connecting technical decisions to business outcomes. Workloads that consume excessive CPU or MIPS don’t just affect system performance—they increase operating costs and can create resource contention that impacts critical business processes.
Incremental or All at Once Mainframe Modernization
Modernization is rarely an all-or-nothing effort. Very few organizations have the budget, resources, or business appetite to modernize everything at once.
The customers I see making the most progress are taking an incremental approach. Too often, organizations investigate performance only after something has gone wrong. By then, technical debt has already affected the business.
“Modernization is rarely an all-or-nothing effort. Very few organizations have the budget, resources, or business appetite to modernize everything at once.”
In contrast, ongoing visibility allows teams to identify workloads that are gradually becoming less efficient and address issues before they become operational problems. This approach lowers risk, builds confidence, and enables modernization efforts to proceed without disrupting mission-critical operations.
I’ve also found that modernization becomes much easier when teams have the right tools to support it. Developers are understandably reluctant to modify business-critical applications if they can’t see the downstream impact of their changes or validate those changes before deployment.
Modern development environments, automated testing, and dependency-aware development practices give teams the confidence to improve applications safely. Instead of avoiding change because the risk feels too high, teams can modernize incrementally while preserving the business logic that continues to deliver value.
The most successful modernization efforts are built through hundreds of well-informed decisions made over time.
How Should Enterprises Treat Ongoing Technical Debt
The pace of change isn’t slowing down. AI, automation, evolving regulations, and new business expectations will continue to reshape enterprise IT.
Even with all this change, technical debt will persist. The challenge is whether an organization can manage it strategically. Effectively managing it starts with understanding the environment you have today.
“The most successful modernization efforts are built through hundreds of well-informed decisions made over time.”
Organizations with a clear view of their applications, infrastructure, and dependencies are in a much stronger position to make informed decisions about where to modernize, where to optimize, and where to preserve the systems that continue to deliver business value. They can adopt new technologies with greater confidence because they understand the impact those changes will have across the enterprise.
Mainframes have remained at the center of enterprise computing for decades because they’ve continuously evolved alongside the businesses they support. I believe the same mindset applies to modernizing technical debt as a whole.
The future belongs to organizations that treat modernization as an ongoing discipline, not a one-time initiative, balancing innovation with stability while continuing to invest in the mission-critical systems that power their business.
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