What is tech debt?

What you need to know

In 1992, at an Object-Oriented Programming, Systems, Languages and Applications conference, Ward Cunningham explained it: “Shipping first-time code is like going into debt. A little debt speeds development so long as it is paid back promptly with refactoring. The danger occurs when the debt is not repaid.”

Since then, the term has taken on many different meanings and transcended its original domain—code—to include other parts of an enterprise system such as infrastructure, enterprise architecture and processes that haven’t been adapted to work effectively with modern IT systems and technologies. As organizations navigate rapid technological changes, the concept of tech debt has become increasingly significant.

Tech debt is not just about technical issues but also about cultural shifts within organizations. It encourages a balance between short-term gains and long-term sustainability, promotes continuous learning and upskilling, and supports the mental health of developers.

The sense among many tech leaders is that we are riding a surge of tech debt—an impression that is confirmed by our Digital Core report. In the US alone, tech debt costs $2.41 trillion a year and would require $1.52 trillion to fix.

What’s driving the surge in tech debt?

A combination of factors. Technology departments are moving to always-on, evergreen IT solutions. As technology is changing so rapidly, tech leaders find they are working toward faster response times: issues that they previously would spend months analyzing now require a response in weeks. Meanwhile, macro-economic headwinds and geopolitical instability are throwing up new issues for businesses.

How does managing tech debt empower organizations?

Organizations that effectively manage tech debt are likely to see enhanced agility, higher software quality, and increased innovation. They are better positioned to attract top talent who seek well-maintained codebases and purpose-driven development. Companies that invest in continuous refactoring and modernization are more likely to outperform their competitors in terms of product quality and customer satisfaction. More specifically, based on our latest research, companies need to allocate the “just right” amount of about 15% of their IT budgets to remediate technical debt, especially for new IT projects. Further, companies with lower-than-average tech debt have performed better than their peers in revenue growth and expect better performance in the next three years (5.3% vs. 4.4% 2024-2026). 

What are the challenges?

The technical debt between different systems can exacerbate some issues if not addressed properly. Developers need ongoing training to build their skills in modern development practices and understand how their work contributes to innovation, which requires proactive measures such as training programs and mentorship. Additionally, maintaining code quality and developer engagement in a fast-paced environment demands innovative solutions and constant adaptation.

While traditional IT systems have been accumulating technical debt for decades, our research reveals that AI is now a leading contributor to this issue. Given the rapid growth potential of AI-related debt, companies must proactively address technical debt—the financial and operational costs required to keep IT systems current and aligned with business needs—to sustain evergreen IT capabilities. The same technologies that are contributing to tech debt—AI and generative AI—are also powerful tools for managing it. [See What is generative AI?] 

Suboptimal integration strategies are partly to blame. On top of this, companies often don’t have a security architecture that can handle both people and AI agents working on IT systems. Or, in some cases, companies have platforms that were built with human interactions in mind and aren’t ideal today for many generative AI implementations. Together, these challenges negatively impact the maturity of a company’s digital core. When optimized, a digital core is one of the single biggest drivers of success in a company’s efforts to continuously reinvent itself in the age of generative AI.

What’s at stake?

Technical debt’s impact on tight IT budgets is one thing. The more strategic concern is that tech debt is affecting their ability to create new business and it is sapping their ability to respond to shifting market conditions.

Technical debt hampers development cycles, with developers dedicating more time to bug fixes, conflict resolution, and navigating complex codebases. It also elevates the risk of system failures, security vulnerabilities, and performance issues. Furthermore, tech debt can stifle innovation, as resources are diverted to managing and maintaining current systems instead of exploring new ideas and technologies.

Break free from debt

Our digital core report found that leading companies allocate, on average, 15% of the  IT budget toward tech debt remediation. [See What is Digital Core?] This balances debt reduction while also prioritizing future strategic innovations. This requires a commitment to continuous updates, upgrades and management of end-user software, hardware and associated services to mitigate the technical debt that resides in these systems. 

Within this, we recommend three concrete actions to effectively balance tech debt. Companies who take these actions will have better insight into whether generative AI is a net-positive factor from a tech debt perspective, and they can develop remediation strategies accordingly.

• Focus on the principal: Categorize your tech debt to identify and prioritize the principal amount. This will prevent interest accruing that will lead to more liabilities and hamper new opportunities.
  
  
• Trace your debt to source: Create a tech debt inventory to track your debt and use our value-based framework to prioritize what needs to be urgently remediated.
  
  
• Use the right metrics: You can’t manage what you can’t measure. For example, at the software code level, companies should use tech debt density, which is measured as cost per line of code. It’s a better reflection of your code's health—much like GDP per capita is a better indicator of a country’s development than GDP alone.

By addressing tech debt and building a modern infrastructure, organizations can drive innovation. A modern digital core, leveraging cloud technologies, data, AI, and open architectures, enables operational excellence, cost efficiency, personalized customer experiences, and faster time to market.