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Together with TechStrong, we surveyed 2,600 DevOps professionals to understand their current and planned use of AI-augmented DevOps technologies. Learn what your peers had to say about the value of AI in DevOps, where in the DevOps pipeline they expect to see the greatest benefits, and what challenges they hope this technology will help them overcome.
Across all survey participants, testing is where organizations are hoping to see the greatest value from AI-augmented DevOps, with nearly 70% of respondents rating the potential of AI-augmented testing as extremely or very valuable. This should come as no surprise: Testing involves large amounts of complex testing scenarios and test data and many organizations struggle to scale test automation to the level their DevOps environment requires. This presents a major pain point for DevOps organizations, who are keen to apply new technologies like AI to help improve testing speed and scalability.
When we asked respondents what types of testing they were struggling to automate most—and where they thought AI-augmented technology could help the most—functional testing ranked first. According to one respondent, “Most organizations today, including mine, still depend heavily on manual testing; mainly because traditional automated test scripts require too much time to maintain and quickly become unreliable. Today, AI-augmented DevOps is well-suited for automating specific types of testing including unit testing, functional testing, UI testing and performance testing. The big advantage is the time saved.”
Across the board, survey respondents had high hopes for the future of AI-augmented DevOps, expecting it to deliver meaningful benefits in a variety of crucial technology and business areas. They include:
It’s clear: DevOps teams are excited about AI, both for the benefits it affords today and for its future promise. The time is now for organizations at every stage of maturity to begin incorporating AI technology into their software planning, development, testing, deployment, and operations practices.
