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19/08/2026 3:57 pm
TL;DR: AI is compounding technical debt by increasing the volume of code teams must verify, with Sonar reporting that 88% of developers see negative debt impacts and 42% of committed code is now AI-generated or assisted, while 93% also see cleanup benefits. The practical issue is not AI itself but whether organisations can enforce continuous code verification and quality gates before unreliable or duplicative code becomes operational debt.
NHIMG editorial — based on content published by Sonar: Managing technical debt in software development
Questions worth separating out
Q: How should teams control technical debt in AI-assisted development pipelines?
A: Treat AI-assisted code as high-volume change that still needs the same verification standard as human work.
Q: Why does technical debt matter to security teams as well as developers?
A: Because the same shortcuts that slow development also weaken control points that security depends on.
Q: What do teams get wrong about technical debt remediation?
A: They often treat it as a periodic cleanup task instead of an ongoing operating model.
Practitioner guidance
- Enforce merge-time quality gates Block commits that fail reliability, maintainability, or security thresholds, and require the same checks for AI-generated and human-written code.
- Track technical debt as a risk portfolio Classify debt items by severity, remediation effort, and business impact so teams can pay down the highest-interest items first.
- Review identity-sensitive code with extra scrutiny Require deeper review for changes that touch authentication flows, service accounts, tokens, or secrets embedded in code or build pipelines.
What's in the full article
Sonar's full report covers the operational detail this post intentionally leaves for the source:
- Survey breakdowns on how developers experience AI-generated technical debt in day-to-day delivery
- Specific examples of reliability, duplication, and debugging issues that the report attributes to AI-assisted code
- SonarQube quality gate and remediation workflow detail for teams that need implementation guidance
- The article's fuller discussion of AI's positive role in documentation, testing, and refactoring
👉 Read Sonar's analysis of how AI is changing technical debt management →
AI-generated code and technical debt: are your controls keeping up?
Explore further
19/08/2026 4:35 pm
AI debt is becoming an assurance problem, not just a productivity problem. When AI increases code volume, the bottleneck moves from creation to verification. Teams that treat generated code as inherently reviewable are underestimating how quickly hidden defects and duplicated logic can accumulate. The practical conclusion is that code assurance now needs to be continuous, not episodic.
A question worth separating out:
Q: How do organisations know if verification is working well enough?
A: They should look beyond pass rates and review operational signals such as manual review volume, abandonment during verification, exception approvals, and repeated re-checks for the same identity. If the process is accurate but creates excessive friction or bypass behaviour, it is not functioning as a reliable control.
👉 Read our full editorial: AI-generated code is accelerating technical debt and review risk
