Usage, Effects and Requirements for AI Coding Assistants in the Enterprise: An Empirical Study

AI-powered coding assistants are becoming ubiquitous, intimately embedded in software development process. The rise of large lan- guage models (LLMs) has accelerated the development of automated techniques and tools for supporting various software engineering tasks, e.g., program understanding, code generation, software test- ing, and program repair. As CodeLLMs are being employed toward automating these tasks, one question that arises, especially in en- terprise settings, is whether these coding assistants and code LLMs that power them are ready for real-world projects and enterprise use cases. In this paper we survey 57 developers from different domains and with varying software engineering skill about their experience with AI coding assistants and CodeLLMs. In parallel, we reviewed 35 user surveys on the usage, experience and expec- tations of professionals and students using AI coding assistants and codeLLMs. Based on our study findings and analysis of exist- ing surveys, we discuss the requirements for AI-powered coding assistants.