- Stduy claims AI adoption outpaces governance, creating long-term code maintainability challenges
- Saved developer time is now being spent on reviewing, validating and governing AI
- Accountability and trust are now more important than speed and productivity
Even though 91% of organizations have two or more AI coding tools in active use, four-fifths (79%) of the more than 1,500 developers surveyed by GitLab believe software delivery hasn’t accelerated at the same pace as developer productivity, implying challenges along the workflow could be diminishing returns.
Around three in four believe developers are writing code faster (78%) and producing higher-quality code (73%), but a new report from the coding platform believes there’s much more to AI than speed alone.
GitLab describes this as an ‘AI paradox’, where developer time is being taken up reviewing, validating and governing AI despite its promised productivity impacts.
Is AI just shifting problems downstream?
In fact, 85% agree that the biggest constraint now is code review and validation, rather than code creation, proving that problems have simply been moved downstream instead of removed entirely.
But now that AI is deeply engrained within developer workflows, two in five (43%) now struggle to distinguish AI-generated code from human-written code, making it difficult to maintain security and quality in the long term. Three in four (73%) say they’re concerned about the long-term maintainability of AI code.
And it’s this visibility that’s causing one of the biggest headaches for coders, with a third (34%) now unable to determine whether AI-generated code played a role in an incident.
“The events of the past few months, including supply chain attacks, reliability issues, and regulators tightening expectations around AI traceability and provenance are making clear that speed without control is a liability, not an advantage,” Chief Product and Marketing Officer Manav Khurana commented.
Most companies (92%) now experience some form of governance challenges when it comes to vibe coding, and four in five admit they’ve adopted AI coding tools faster than they’ve implemented governance policies.
Trust to become a key differentiator – not speed
While coding has become a major use case for generative AI since its mainstream introduction in late 2022, policies are still falling behind. But developers know this, and 91% now plan to invest in governance over the next year, with 98% allocating budget specifically for this.
Looking ahead, developers are preparing to enter a new era of AI, where generating code is no longer a priority. Instead, it’s all about governance.
“Organisations that will ship trusted software faster are the ones building the foundations of accountability with context, traceability, and governance baked into the platform, not just bolted on after the fact,” Khurana added.
But reading between the lines, it’s been clear that developers haven’t been entirely comfortable with AI for some while. Stack Overflow’s 2025 developer survey found that many are turning their backs on the tech due to privacy, pricing and quality reasons. Nearly 46% distrust AI to some degree, compared with just 33% who trust it.
Developers have now reached a point where AI has very clear use cases, but GitLab’s report clearly shows that traceability, accountability and trust will become competitive advantages in the future.
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