AI and DevOps: enhancing, not replacing

AI is being used alongside existing DevOps practices, with reported impacts on testing processes and role responsibilities, while governance gaps and cloud and energy costs remain considerations.

Perforce Software has released findings from its 2026 State of DevOps Report, examining the relationship between AI and DevOps and how AI is influencing software development practices. The survey gathered responses from 820 technology professionals worldwide, 54% of whom hold C-level roles. The report explores questions including whether AI could replace traditional DevOps practices and how AI is affecting roles, governance, and operational costs.

The report identifies a relationship between AI and DevOps rather than suggesting that AI replaces existing practices. According to Anjali Arora, CTO of Perforce, the research indicates that organisations with established engineering practices, including automation, collaboration, governance, and auditability, are more likely to scale AI initiatives and connect them to business outcomes.

The study reports that organisations with more mature DevOps practices are generally more successful in embedding AI within their software delivery lifecycle. According to the survey, 70% of respondents say DevOps maturity materially affects AI success. AI adoption across the software delivery lifecycle differs by maturity level:

  • 72% AI embedded in high-maturity organisations
  • 43% AI embedded in mid-maturity organisations
  • 18% AI embedded in low-maturity organisations
The report also examines how AI is affecting roles within DevOps teams, particularly in testing. Survey responses indicate that:

  • 87% believe AI will allow engineers to spend less time on scripting and more on system design and directing outcomes
  • 55% of QA teams report increasing their focus on quality analytics rather than test execution
  • 41% report QA teams evolving into Quality Engineering (QE) roles with a focus on orchestration across pipelines, environments, and data
Respondents report confidence in AI outputs, with 77% identifying benefits such as operational efficiency and improved developer experience. However, the report also notes gaps in governance and oversight. Only 39% of organisations report having automated audit trails in place. Cloud and energy costs were also cited as considerations, with 37% of respondents identifying them as limiting factors for AI adoption.

The survey was conducted in November and December 2025 across North America, the UK and Europe, Latin America, and Asia Pacific. The findings suggest that organisations adopting AI within software development environments often rely on established DevOps practices and governance frameworks. The report highlights areas such as governance, cost management, and operational maturity as factors influencing how organisations adopt AI within DevOps environments.
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