A survey of 504 DevOps practitioners finds a third (33%) are working for organizations that make use of artificial intelligence (AI) to build software, while another 42% are considering it. Only 6% said they have no plans to use AI.

Conducted by Techstrong Research, an arm of the Techstrong Group, the survey, however, finds only 9% have fully integrated AI into their DevOps pipelines. Another 22% have partially achieved that goal, while 14% are doing so only for new projects. A total of 28% said they expect to integrate AI into their workflows in the next 12 months.

Mitch Ashley, principal analyst for Techstrong Research, said it’s clear AI is rapidly establishing a presence across the software development lifecycle (SDLC). AI, especially generative AI, is already improving software testing and code creation and in many cases is helping teams mature their DevOps workflows, he added.

Each organization will naturally adopt AI as they best see fit, but it’s no longer a question of whether to use AI as much as to what degree to rely on it. While AI coding tools make developers more productive, organizations need to make sure the code being created is thoroughly reviewed before incorporating it into a production environment. AI platforms such as ChatGPT were trained using samples of code of varying quality collected from across the Web. In some instances, the code generated might therefore include a vulnerability that could be easily exploited.

In addition, the type of code being generated matters. While an AI platform might easily create a script that can be added to a DevOps pipeline, the quality of business logic it might create might not be neatly as reliable.

Fortunately, the next wave of generative AI platforms is being trained on data for specific domains that have been closely vetted. Many of these platforms will not only generate more reliable code; they will also be smaller than a general-purpose LLM that was used to create, for example, ChatGPT.

Additionally, AI agents that have been trained to automate specific tasks will soon be incorporated into DevOps workflows. As these tasks become increasingly automated, DevOps teams will soon be orchestrating multiple agents that will enable them to build and deploy software at levels of scale that not too long ago would have been deemed unimaginable. DevOps teams should already be creating a list of tasks that will soon be performed by AI agents to better understand how their roles will evolve.

It’s not likely that generative AI is going to replace the need for application developers and software engineers any time soon. However, their roles within organizations will never be the same. The truth is that while AI may be worrisome from a job security perspective most DevOps professionals going forward are not going to want to benefit from it. After all, there are plenty of tedious tasks that ultimately only serve to burn DevOps teams out that, all things considered, could be better handled by a machine.

For more information, download a copy of the DevOps Next report here.