Recommended Free Tools
CIOs struggle to make technical debt a priority because its costs are spread across maintenance, delays, risk, and integration work, while AI, cybersecurity, and growth initiatives give boards more visible outcomes to fund. The practical answer is not to pitch debt reduction as a standalone cleanup project: connect specific fixes to business priorities, then rank them by risk, cost, and measurable benefit.
What technical debt includes—and why it is hard to see
Technical debt is the accumulated cost and constraint of technology choices that make future work harder or riskier. It can include old applications, bloated code, aging hardware, unsupported systems, redundant platforms, and unmanaged data dependencies. It is not limited to software that is visibly broken.
Its effects often appear somewhere other than the asset that caused them: a project needs extra integration work, a team spends more time maintaining a system, a change takes longer to deliver, or an unsupported component cannot receive a security patch. That makes the total burden difficult to present as one bill.
Why CIOs know the cost but still lose the budget argument
Boards and CEOs press technology leaders for visible progress on AI, cybersecurity, innovation, resilience, and revenue. Technical debt is usually less visible until it obstructs one of those goals. As Daniel Saroff, group vice president for consulting and research at IDC, put it: “It’s not a sexy subject,” he says. “It’s not a subject the board are pounding their fists over.”
Crashes, No Sound, or Screen Glitches?
Random freezes, missing sound and display glitches usually trace back to one bad driver. Find and replace yours safely.Free scan · under a minutePC Slower Than It Used to Be?
A free scan shows the junk files, broken settings and background clutter dragging Windows down - then fixes them in one click.Free scan · Windows 10 & 11#1 Best Overall
That mismatch does not mean debt is inexpensive. In IDC’s Future Enterprise Resiliency and Spending Survey, Wave 3, conducted in March 2024, 38% of IT professionals expected to overspend on digital infrastructure; among respondents who expected overspending, 47% attributed it to excessive technical debt, as reported in CIO/IDC analysis.
IDC’s 2023 CIO Sentiment Survey findings, published by IDC in 2024, reported that organizations allocated an average of 12.8% of their IT budget to reducing technical debt, while 79% reported having no formal process for tracking and reporting it. These figures describe survey findings, not a universal cost benchmark: they do not establish how many dollars a particular organization should spend or what its debt will cost.
How to make a board-ready case for modernization
Ask for funding to achieve a business outcome, not simply to replace old technology. For example, if a customer-intimacy program depends on integrating data across several databases, explain how replacing an old ERP could reduce that integration burden and enable the program. Link each proposed remediation to a concrete goal such as security, resilience, faster delivery, cleaner data, lower operating effort, or revenue.
- Connect the work to a funded priority. Show how a specific debt item impedes an AI, cybersecurity, digital-transformation, ERP, mainframe, or customer initiative. State the consequence of leaving it in place.
- Build an inventory. Record applications, hardware, data stores, platforms, and development tools. Include business owner, business criticality, dependencies, vendor-support status, operating or maintenance burden, and known risks where those details are available.
- Identify candidates for action. Flag unsupported, redundant, high-cost, high-risk, or integration-constrained assets. Ask where monthly spending is concentrated and what return the business receives. Ricardo Madan, senior vice president for global technology services at TEKsystems, describes the approach this way: “We just try to take an inventory and look for the redundancies and get those smart CIOs to really ask the right questions: ‘What’s not working well, where is most of your monthly budget going, and what’s the return that you’re getting?’”
- Rank the candidates against business impact. Compare business criticality, security exposure, agility gained, data and integration dependencies, maintenance cost, support status, implementation duration, replacement cost, near-term return, long-term savings, and revenue enablement. Make assumptions visible rather than treating an estimate as a guaranteed saving.
- Present a phased investment and its checkpoints. Separate near-term benefits from longer-term savings or revenue effects. For major modernization, show the architecture, design, milestones, and decision points where leaders can review results and course-correct.
A useful board proposal makes the trade-off explicit: what the organization gains by acting, what risk or cost remains if it waits, what the work will require, and how progress will be measured. The business case should include both near-term ROI and longer-term effects; a multiyear program should not imply that all benefits arrive immediately.
Which legacy systems should be fixed or retired first?
Start with assets that create the most consequential constraints, not simply the oldest assets. A reliable older system may be worth keeping if replacement costs exceed the benefit. Conversely, an unsupported system with meaningful security exposure can deserve attention even if it still appears to function normally.
- Escalate unsupported technology when the lack of vendor support leaves security vulnerabilities that may not be patchable.
- Prioritize high business criticality when an asset supports essential operations or a strategic program and its failure or delay would have material consequences.
- Target recurring cost and redundancy when duplicate platforms or applications consume budget without a clear return.
- Address integration and data bottlenecks when they slow delivery, obstruct modernization, or limit the usefulness of data.
- Defer low-impact replacement when the system remains reliable and the expected benefit does not justify implementation and replacement costs.
Use the same criteria to compare retirement, remediation, and continued operation. Retirement is not automatically best: dependencies, data migration, implementation duration, and the cost of replacement can change the decision. The goal is to reduce debt that demonstrably drains resources, increases risk, delays work, or blocks agility—not to eliminate every old system.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Should technical debt be fixed before launching AI?
Not necessarily all of it. AI work can make data quality and dependencies more visible, so the organization should identify and address debt that would undermine the specific AI use case. Ricardo Madan says: “It’s like a truth serum,” he says. “AI will let you know what that data state is.” That is a reason to assess relevant data and systems, not proof that every legacy platform must be replaced before any AI project can begin.
Map the use case to the applications, data stores, and integration paths it depends on. Then resolve material blockers—such as unmanaged dependencies or data problems that prevent the intended work—while keeping unrelated modernization in a separate, prioritized plan. This avoids both extremes: treating AI as a reason to ignore foundational problems, or making complete debt elimination a precondition for all AI activity.
Best Value
Why modernization needs a plan, not a switch
Replacing a core application or infrastructure can itself introduce operational and delivery risk. Treat large efforts as multiyear programs with architecture, design, sequencing, and checkpoints that let leaders adjust as dependencies and outcomes become clearer. Tim Beerman, CTO at Ensono, cautions: “These things aren’t flipping a switch,” he says. “You need to have an architecture, design, and plan that allows you to course correct along the way.”
For security-sensitive work, the case can be especially direct: unsupported hardware or software may leave vulnerabilities that cannot be patched. Beerman notes: “In today’s market age where cybersecurity attacks are on the rise, hardware and software that’s not supported obviously leads to vulnerabilities that maybe can’t be patched,” he says. Tie that exposure to the affected asset and business risk rather than assuming every legacy system carries the same level of danger.
Quick Recap
Product prices and availability are accurate as of the date/time indicated and are subject to change. Any price and availability information displayed on Amazon at the time of purchase will apply.
