AI transforming DevOps: Tricentis 2024 report reveals impact

Tricentis has unveiled the findings of its latest report, titled "AI-augmented DevOps: Trends Shaping the Future." The research investigates how AI is transforming DevOps practices and identifies the key areas where its benefits are being realised. This follows a similar study conducted in 2022.

The 2024 research surveyed over 500 DevOps practitioners, managers, and executives from a diverse range of sectors including financial services, healthcare, and manufacturing. The survey participants hailed from small, mid-size, and large enterprises globally.

Among the key findings, 60% of DevOps practitioners ranked testing as the most valuable area for AI investment across the delivery cycle. This trend was anticipated in Tricentis' 2022 study, where 70% of respondents had identified AI-augmented testing as highly valuable. "AI is an exciting technology and growing at a pace unlike anything we've seen in our industry," said Mav Turner, Chief Product and Strategy Officer at Tricentis.

The report indicates that mature DevOps teams that have adopted AI are 30% more likely to rate their teams as either extremely or very effective. The primary challenges these teams use AI to tackle include developer team efficiency (60%), reducing the skills gap (54%), cost reduction (47%), and software quality (42%).

A significant portion of respondents estimate that AI-augmented DevOps tools could save teams more than 40 hours per month, which is roughly equivalent to an entire workweek. The 2024 data shows AI is being used to enhance various testing tasks, including test planning (47.5%), test case generation (44%), and analysing test results (32%). Furthermore, nearly half (42%) of respondents expect AI to perform risk analysis of code changes, thereby assisting QA teams in focusing on areas with the highest error risks.

The survey also explored the impact of regulations on AI. Nearly two-thirds (63%) of those surveyed believe that increased regulation will build trust in AI, though 16% of respondents worry that it may stifle innovation. Additionally, AI skills' shortfall remains a significant hurdle, with 28% of respondents viewing it as the greatest barrier to AI adoption in DevOps.

generative AI (GenAI) and AI copilots have emerged as key drivers for AI adoption. GenAI is currently the most widely adopted type of AI among DevOps practitioners, with 45% of respondents using it. AI copilots are also gaining traction, with applications in planning, code development, and software testing.

Mav Turner also emphasised the importance of training in AI adoption. "As AI technology is further developed, however, training software development and quality engineering teams with the necessary skills to effectively work with AI will be absolutely critical," Turner stated. He further highlighted the benefits of integrating AI into testing processes, suggesting that AI can help detect, auto-heal, and predict defects during development.

The report underscores that human involvement remains essential in ensuring software quality. Over two-thirds (71%) of practitioners checked AI outputs at least half the time, with nearly one in five (19%) checking AI outputs all the time. This confirms the need for balanced integration of AI and human expertise.