AI isn’t killing DevOps, you’re just using it wrong

AI hasn’t rendered traditional DevOps practices obsolete, new research suggests, but only enterprises with mature practices are recording success with the technology.

According to Perforce’s 2026 State of DevOps Report, 70% of organizations say DevOps maturity materially affects AI success. Indeed, those with mature processes are finding it easier to integrate the technology across the software development lifecycle (SDLC).

Nearly three quarters (72%) of high-maturity organizations told Perforce they’ve successfully embedded the technology in processes, compared with 43% of mid-maturity companies and 18% of low-maturity firms

"The market often asks whether AI will replace DevOps. Our research shows the opposite: AI amplifies DevOps," said Anjali Arora, CTO of Perforce and author of the report.

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"Organizations with disciplined engineering practices, automation, strong collaboration, and focus on control, auditability, and governance are the ones scaling AI successfully and turning innovation into measurable business outcomes."

How AI is changing DevOps practices

AI is changing roles in DevOps, researchers found, particularly in testing. The vast majority of respondents (87%) believe that AI will enable engineers to focus less on scripting and more on system design and directing outcomes.

More than half (55%) of QA teams have increased their focus on quality analytics rather than test execution, and 53% said developers author tests directly.

Nearly half (41%) reported that QA teams are also evolving into Quality Engineering (QE) teams, with 39% citing a focus on orchestration across pipelines, environments, and data. Meanwhile, 38% said that business analysts are involved in test creation.

"The research confirms what we are already seeing: AI is helping teams shift up from execution to oversight and strategy, effectively elevating individual roles," said Jake Hookom, EVP of product at Perforce and report author.

"But the research also highlights that governance and auditability need to be a focus for organizations and the collaboration between teams."

Devs are starting to trust AI

Confidence in AI appears to be improving among DevOps teams, Perforce researchers found. More than three quarters (77%) said they have confidence in AI outputs, for example.

Meanwhile, 74% said AI was meeting or exceeding expectations, with 50% measuring AI's value through customer retention or acquisition, 48% seeing faster delivery, and 44% citing revenue or market share impact.

Perforce did warn that governance is often fragmented and incomplete, posing significant challenges for many enterprises. Compliance oversight is split between multiple functions, and only 39% have full automated audit trails, making measurement expensive and inconsistent.

Notably, 74% said that cloud/compute costs and energy usage influence their organization's decisions about AI adoption, and 37% cite these as limiting factors.

"DevOps practices are widespread but uneven. This split explains why DevOps is simultaneously described as 'solved' and 'broken'," the researchers conclude.

"For organizations with mature practices, DevOps works. For those with incomplete implementations, it doesn't. AI doesn't change this dynamic. It amplifies it, widening differences in outcomes, reliability, and cost."

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