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Last month at Google I/O 2025, we shared our vision for a reimagined, AI-first Colab, a true coding partner in your notebook designed to help you tackle your most challenging problems faster than ever. We’ve started by rolling these features out to a small group of users, and the response has been incredible. Today, we are thrilled to make AI-first Colab available to everyone!
Early users have been embracing Colab’s new agentic capabilities to accelerate their projects, learn new skills, and unlock insights from their data in ways that have delighted and inspired us.
From early access to everyday productivity
Our goal was to build an AI collaborator that understands your intentions and integrates seamlessly into your workflow. Based on user feedback, this new experience is already making a significant impact.
Here are a few of the top ways people are using the new Colab AI:
1: Accelerating End-to-End Machine Learning Projects
Users are leveraging Colab AI for the entire machine learning lifecycle. From taking a raw dataset and asking the agent to autonomously perform cleaning and preparation, to generating feature analysis, training models, and evaluating the results. This turns hours of work into a guided, conversational experience.
2: Smarter Debugging
Coding is an iterative process. Colab AI acts as a pair programmer to help you prototype ideas, generate boilerplate code, and understand new libraries. When you hit an error, the AI doesn’t just help find the bug, it can suggest a fix in a clear diff view, helping you learn and keep going with your project. The result is a massive boost in productivity.
3: Creating Stunning Visualizations with Zero Hassle
Data exploration is incomplete without visualization. Users are simply asking Colab AI to graph their data, and it generates high-quality, clearly labeled charts without the need for manual tweaking of plotting libraries.
A quick look at the features powering your workflow
These use cases are powered by a suite of new, deeply integrated features:
- Iterative Querying: A conversational experience where you can ask for code, get explanations about libraries, and intelligently fix errors.
- Next-Generation Data Science Agent (DSA): Trigger autonomous analytical workflows. The agent creates a plan, executes code, reasons about the results, and presents its findings, all while allowing you to provide feedback and stay in control.
- Effortless Code Transformation: Simply describe a change in natural language, and Colab will identify and refactor the relevant code for you.
Get started with Colab AI today!
We are incredibly excited to put these powerful new capabilities into the hands of the entire Colab community. This is a major step in our journey to create a more powerful and intuitive AI-first Colab, and we’re just getting started.
Ready to try it out? It’s easy to get started:
1: Open any new or existing notebook in Google Colab.
2: Look for the Gemini spark icon in the bottom toolbar.
3: Start asking questions and giving commands!
We can’t wait to see what you build. To share your feedback and connect with other users, please join our Google Labs Discord community and the #colab-ai channel.
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