A global survey of 705 developers and IT leaders finds 42% of respondents reporting that artificial intelligence (AI) now writes at least half their code, with only 21% of developers now spending more than half their week writing new code from scratch.

Conducted by BairesDev, a provider of software development services, the survey also finds nearly 80% of developers now spend less than half their week coding. As a result, developers on average are saving 13 hours a week on coding, allowing them to devote more time to reviewing AI output (67%) and debugging it (52%).

Developers are also now spending, on average, nine hours a week learning AI tools and new technologies. That investment appears to also be paying off, with AI tool fluency (29%), system architecture (20%), and human skills (15%) expertise driving pay increases for developers, the survey finds.

A full 86% of respondents also report they now find their role in their organization more fulfilling, according to the survey. In addition, 51% of developers noted that accountability for AI-generated code sat with them personally.

BairesDev CTO Justice Erolin said that while AI has transformed coding, the rest of the software development lifecycle remains a work in progress. For example, only 7% of developers said the ship decision has been entirely delegated to AI without their input. Another 32% said it has been delegated to AI with a developer in the loop.

It’s not clear at what pace DevOps teams are re-engineering workflows for the agentic AI era, but the amount of code being created is clearly starting to overwhelm existing pipelines. Ideally, DevOps teams will be relying more on AI agents to manage those pipelines, but for the moment, at least the pace at which applications are being deployed has not exponentially increased. Organizations are definitely generating more code than ever, but the percentage of it that winds up being deployed in a production environment differs widely from one team to the next.

The one thing that is apparent is that humans won’t so much be in the middle of the DevOps loop in the AI era so much as they will be observing and supervising the activities of AI agents, noted Erolin. Otherwise, human engineers will eventually become just another bottleneck slowing down the pace at which software is built and deployed, he added. At the same time, AI agents that are not properly governed will simply run amok in ways that would be too difficult for most DevOps teams to discover and contain on their own, noted Erolin.

Of course, re-engineering DevOps workflows will require some level of additional investment. In some cases, that may simply come in the form of additional training for software engineers. However, many organizations will also be revisiting the continuous integration/continuous deployment (CI/CD) platforms that were not designed for the agentic AI era.

Regardless of approach, there is at this juncture no going back. The challenge and the opportunity now is determining how best to employ AI agents to safely deploy more software at a scale that a few short years ago would have seemed unimaginable.