AI Tools for Kotlin Developers: What You Need to Know in 2025

AI Tools for Kotlin Developers: Overview of Current Solutions

Kotlin has firmly established itself as a modern cross-platform language — from Android applications to server-side solutions and multiplatform projects. In 2025, the Kotlin developer's toolkit has been enriched with powerful AI assistants that can not only autocomplete lines of code but also generate entire functions, suggest refactoring, and automate writing tests. We have gathered the key tools worth integrating into your workflow.

1. GitHub Copilot (with Extended Kotlin Support)

The market leader among AI assistants — Copilot from GitHub and OpenAI. After the update to the GPT-4o-based version, the model has become significantly better at understanding Kotlin specifics: coroutines, sealed classes, extension functions, and DSL syntax. Copilot works in IntelliJ IDEA, Android Studio, and VS Code. It offers autocompletion in entire blocks, helps write unit tests in Kotest or JUnit, and even suggests architectural solutions for Jetpack Compose.

2. Tabnine (Enterprise Solution for Teams)

Tabnine focuses on code security and training on private company repositories. For Kotlin projects, Tabnine excels at generating boilerplate code for Data classes, Room entities, and Retrofit interfaces. An important advantage is that it works completely locally (optionally), which is critical for projects with closed-source code. Tabnine also supports contextual refactoring and code smell detection.

3. JetBrains AI Assistant (Native Integration)

The creators of Kotlin — JetBrains — have released their own AI assistant, built directly into IntelliJ IDEA and Android Studio. It uses both local models and cloud-based ones (GPT-4, Claude). Its specialty: deep integration with the Kotlin ecosystem. The assistant understands the specifics of Ktor, Exposed, kotlinx.serialization, and offers solutions that are optimal specifically for Kotlin, rather than generic Java patterns. A chat is available for documentation questions and code generation.

4. KAI — Kotlin AI (Specialized Model)

A relatively new player — KAI, a model trained exclusively on Kotlin code and its libraries. KAI excels at tasks where general models make mistakes: correct work with coroutines, proper use of Flow and Channel, and code generation for KMP (Kotlin Multiplatform). KAI is available as a plugin for IntelliJ IDEA and as a standalone CLI tool. It is especially useful for Kotlin Multiplatform Mobile projects.

5. Sourcegraph Cody (Contextual Assistant)

Cody is an AI assistant that understands the entire project codebase, not just the current file. For large Kotlin projects, this is a lifesaver: it can explain how legacy code works, find all places where a specific class is used, and suggest refactoring considering the entire application architecture. It supports commands like "write a test for this module" or "find a bug in this method".

How to Choose a Tool?

• For individual development: GitHub Copilot or JetBrains AI Assistant — the best start. Copilot is cheaper, JetBrains is more deeply integrated.
• For teams with private code: Tabnine (local mode) or Sourcegraph Cody.
• For complex Kotlin-specific tasks (KMP, coroutines): KAI or JetBrains AI