Understanding AI Coding in ATLAS.ti Web

With AI Coding, you can guide ATLAS.ti’s Web’s artificial intelligence (AI) as it automatically codes your data. You simply tell ATLAS.ti Web what your research goal is, then let ATLAS.ti Web identify relevant segments of data and apply codes to your data to help you achieve your research goal.

Why use AI Coding in ATLAS.ti Web?

AI-driven tools are now widely available and can facilitate multiple aspects of the research process, including coding qualitative data. However, an important concern quickly emerged when using AI to code qualitative data: the AI does not know what the research question is, so it often creates a large variety of codes that may end up not being relevant to the study at hand. The AI Lab at ATLAS.ti has been working hard to address this concern, resulting in a groundbreaking development for ATLAS.ti’s AI Coding – You can now tell the AI about your research question, objectives, and any relevant contextual details to guide how the AI should code your data! This gives you more control over the AI and helps ensure that the resulting analyses will be relevant to your research question.

How does AI Coding work in ATLAS.ti Web?

1.    Select your text document(s)

To analyze multiple text documents, select your documents from the Document Manager. Then click on three dots at the bottom of the page, select "Tools" and then select "AI Coding". To analyze a single document, you can also open any document and click on Tools and then click on "AI Coding".

2.    Enter your research goal

The first step in ATLAS.ti Web’s AI Coding is to define your research goal. A research goal is a clear statement of what your objective is in your study. 

Your research goal could be about understanding a particular phenomenon or solving a specific issue. For example, in our sample project on sustainability, our research goal is to identify practical suggestions for how people can live more sustainably in their everyday lives.

What is a research goal?

A research goal is a clear statement of your objective in this project: What do you want to understand, or what problem are you addressing? For example, maybe you want to identify practical suggestions for how people can live more sustainably, or you want to analyze how employers can encourage people to be more sustainable at work.  

3.    Guide the AI Coding

Once your research goal is set, ATLAS.ti Web generates a series of related questions. This is where you can guide how the AI will code your data. These questions act like a lens, focusing the AI's attention on extracting data that is most relevant to your specific interests. For example, if we’re analyzing sustainable lifestyles, the AI might generate questions asking about facilitators and barriers to living more sustainably.

ATLAS.ti Web’s AI Coding also displays how it will categorize all the data segments that help answer each question. A code is simply a word or short phrase that describes something in the data, like a tag that you attach to organize your data. Each category is then like a thematic umbrella, and underneath it are more specific sub-codes related to that theme. 

You can now edit questions, remove questions, add more questions, and specify which code category captures the essence of each question. You do not need to edit any sub-codes at this point, because the AI will automatically generate sub-codes that are relevant within each category. 

What is happening here?

ATLAS.ti Web's AI has generated several questions tailored to your research goal. These questions will be used to extract relevant insights from your data and sort them by different categories. ATLAS.ti Web will also attach specific codes (or tags) to further organize the data within each category. For example, to achieve a research goal to identify practical suggestions for living more sustainably, ATLAS.ti Web might generate guiding questions and relevant code categories for suggestions related to life at home and the workplace.  

4.    Review the results

After the AI finished coding your data, ATLAS.ti Web will give you an overview of the results, then you can click "Create quotations". 

To easily review your results, we recommend clicking on "Save as view" to save a view (i.e., report) of the AI Coding results. This view will include the date, time, and all the created codes and their associated data quotations. You can always access this view from your View page, and this view also makes it easy for you to review the codings and make any edits as necessary (e.g., add/remove codes, rename codes, merge codes in the Code Manager, etc.).


AI Coding in ATLAS.ti Web is a robust tool designed to make your qualitative data analysis as efficient and insightful as possible. By understanding and utilizing the concepts of research goals, related questions, and code categories, you can navigate the application seamlessly and achieve deeper insights into your research data. For any further assistance, our Help Center is always available to guide you through your analytical journey with ATLAS.ti.