We found that most of those using code assistant tools report that these assistants are satisfying and easy to use and a majority (but not all) are on teams where half or more of their coworkers are using them, too. These tools may not always be answering queries accurately or solving contextual or overly specific problems, but for those that are adopting these tools into their workflow, code assistants offer a way to increase the quality of time spent working.
The majority of respondents (76%) let us know they are using or are planning to use AI code assistants. Some roles use these tools more than others amongst professional developers: Academic researchers (87%), AI developers (76%), frontend developers (75%), mobile developers (60%), and data scientists (67%) currently use code assistants the most. Other roles indicated they are using code assistants (or planning to) much less than average: data/business analysts (29%), desktop developers (39%), data engineers (39%), and embedded developers (42%). The nature of these tools lend themselves to work well when trained well; a tool such as GitHub Copilot that is trained on publicly available code most likely will be good at JavaScript for frontend developers and not so good with enterprise and proprietary code scenarios that business analysts and desktop developers face regularly.
But go ahead, speak for the whole goddamn industry, we're totally not using AI or AI code-assist!!!!