Gartner defines AI code assistants as tools that generate and analyze software code and configuration. They use foundation models like LLMs, program-understanding technology, or both. Developers engage with these assistants to generate, analyze, debug, test, fix, refactor code, search dependencies, update libraries, create documentation, understand code, upgrade versions, translate languages and review commits. They help developers learn and explore codebases and access related information, such as frameworks and tools. AI code assistants integrate with developer environments, code editors, command-line terminals, chat interfaces, project management tools, monitoring, logging and deployment tools. Some are customized to an organization’s specific codebase and documentation. AI code assistants enhance software developers’ experience by boosting their efficiency, accelerating application development, minimizing cognitive overload, amplifying their problem-solving skills, enabling faster learning, fostering creativity and maintaining their state of flow.
Gartner defines the generative AI (GenAI) knowledge management apps/general productivity submarket as technologies that enable companies to better retrieve and contextualize information and insight from their knowledge bases, including enterprise AI search, conversational AI platforms, and productivity tools for communications and content development.