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Top 5 Tools for AI Thematic Analysis in 2024
Home > Blog >
Top 5 Tools for AI Thematic Analysis in 2024

Top 5 Tools for AI Thematic Analysis in 2024

Kritika Oberoi
May 2, 2024

Qualitative research has always relied on thematic analysis as one of its mainstays for good reason: it helps to identify patterns and find answers in massive sets of information.

But as datasets have become ever more extensive and complex, the manual labor involved in sorting through these facts has grown increasingly overwhelming.

Thankfully, artificial intelligence (AI) is here! This groundbreaking technology provides researchers with faster methods of finding answers in huge amounts of qualitative data.

In fact, it’s already taking over! According to, 77.1% of UX Researchers use AI in at least some of their research projects.

In this post we will explore the topic of AI thematic analysis:

If you’re an expert or just starting out in your field there’s something here for everyone! Stay tuned to learn where things are headed for AI thematic analysis. 🔮

But first thing’s first…

What is thematic analysis?

Thematic analysis is an analysis technique that helps you find patterns and themes in qualitative data. This method can be applied to different forms of information like interviews, focus groups, open-ended surveys, and literature reviews.

Thematic analysis has 4 broad steps:

  1. Familiarizing yourself with the data
  2. Generating codes or themes to organize your data
  3. Reviewing and refining these themes
  4. After a number of iterations, you land on a “definition” of your theme
  5. Writing up your insights!

When to use thematic analysis

Thematic analysis is a commonly used qualitative research method across fields like social sciences, psychology, healthcare, UX research, and market research. 

Thematic analysis has grown even more popular recently because of the increasing availability of qualitative data from online sources, such as social media, blogs, and forums. As the volume of this data continues to grow, researchers are turning to thematic analysis, often in combination with AI tools, to efficiently analyze and derive insights from these rich sources of information.

What is the best software for thematic analysis?

Let’s be honest: the simplest thematic analysis software is an excel sheet.

excel sheets for thematic analysis

But if you’ve got budget for tooling, an enormous amount of data, and a shortage of time (or patience), dedicated software for thematic analysis can be really useful.

Specialized qualitative analysis softwares include Looppanel, NVivo, ATLAS.ti and others. Features typically included in thematic analysis software:

  • Transcription integrated with audio / video
  • Tagging / coding of text
  • Analysis of themes across calls
  • Search capabilities
  • And these days… AI thematic analysis features! (more on this below)

If you don’t want a comprehensive qualitative analysis software, you can also leverage AI chatbots like ChatGPT and to assist you in thematic analysis. These tools won’t provide tagging, transcription, and other qualitative analysis features, but they can still be useful tools for summarization and report writing.

While these programs do cost $$$, they save time when dealing with large scale projects and give better results in the end. The type of software you choose depends on the amount of data  you’re handling along with budgets available to you.

Can you use AI for thematic analysis?

Short answer: Yes!

Many researchers are already using AI for thematic analysis. AI thematic analysis tools utilize advanced algorithms and natural language processing (NLP) techniques to automate laborious tasks, like coding and theme identification, saving researchers significant time and effort.

While it’s tempting to let AI take the wheel, it's also essential to approach AI thematic analysis with a critical eye. AI tools are not infallible!

Researchers should always review and validate the output generated by AI, using their domain expertise to ensure the accuracy and relevance of the identified themes. AI should be seen as a complement to, rather than a replacement for, human judgment and interpretation.

When used judiciously, AI thematic analysis tools—ranging from free, user-friendly options for small-scale projects to sophisticated platforms designed for large datasets—can be a powerful asset to researchers.

5 best AI tools for thematic analysis

1. Looppanel

About the product: Looppanel is a powerful research analysis tool that streamlines thematic analysis. It generates high-quality transcripts for recordings, automatically extracts answers provided by participants, and organizes them according to interview questions. This AI-driven tool also enables researchers to code data by theme, extract video clips of key quotes, and analyze data across multiple calls.

How is AI used in Looppanel?

  • Automatic notes are generated and organized by your interview questions, saving valuable time and effort.
  • AI-assisted tagging is used for thematic coding, helping you identify emerging themes quickly.
  • AI-powered search allows you to quickly find data on any topic, theme, or idea.

Free Trial: Looppanel offers a free 2-week trial

Pricing: Plans start from $30 per month, making it an affordable option for researchers and teams.

Customer Quote: “LoopPanel's automated recording and transcription capabilities are nothing short of revolutionary. The platform seamlessly captures audio data from user interviews or feedback sessions and converts it into accurate transcriptions in real-time.”

Rating on G2: 4.8 stars ⭐⭐⭐⭐⭐

2. ChatGPT

About the product: Unless you’ve been living under a rock, you’ve heard of ChatGPT. ChatGPT is an AI chatbot that you can feed data to (such as your transcripts) and ask for insights or answers to questions. However, because it’s not built for research there are some key limitations:

  • limitations on the amount of text you can input at a time
  • context limits (it forgets context you shared earlier in the conversation)
  • no checks for hallucinations (it can make stuff up!) so you have to check the output carefully

So, can ChatGPT be used for qualitative analysis? Yes, ChatGPT can be used to summarize large amounts of data that you input, helping you identify key themes and patterns. However, it's essential to review and validate the output to ensure accuracy and relevance.

How is AI used in ChatGPT?

  • Summarizing large amounts of data, identifying key themes and insights

Interested? Get started with this list of ChatGPT prompts!

Free Trial: GPT 3.5 is available for free!

Pricing: Better models (GPT 4) and higher usage limits start from $20 per month

Customer Quote: “ChatGPT is its ability to offer diverse and flexible interactions, spanning from answering complex queries to engaging in creative storytelling. It can provide personalized responses, adapt to various tones and contexts, and learn from interactions to better meet user needs.”

Rating on G2: 4.7 stars ⭐⭐⭐⭐⭐


About the product: Claude is similar to ChatGPT, but with better writing skills. You can upload upto 5 documents to Claude for context and ask it to find patterns, re-write insights, and generate codes or themes. You do need to check Claude's output though. Similar to ChatGPT, it’s not built for qualitative analysis and there is a chance it’ll hallucinate or get things wrong. 

While Claude is not a replacement for comprehensive thematic analysis, it can be a helpful sidekick. We’d recommend using it to help surface codes you can use, find quotes for your work, and generate high level summaries of interviews.

How is AI used in

  • Summarizing large amounts of data, identifying key themes and insights

Free Trial: Basic version available for free!

Pricing: Starting $20 / month for greater usage capacity, access to different models and new features

User Review: “What's most useful about Claude is the AI's ability to flow more naturally. I like that responses feel more like human to human conversation. Another thing I like about Claude is that its responses are contextual and engaging. I also like it tries to give accurate responses and acknowledges its limitations when it doesn't know something.”

Rating on G2: 4.7 stars ⭐⭐⭐⭐⭐

4. NVivo

About the product: NVivo is a comprehensive qualitative data analysis software frequently used in academic settings. Built for manual analysis, NVivo has now incorporated AI-powered tools to enhance thematic analysis. It supports a wide range of data types, including text, audio, video, and social media content.

How is AI used in NVivo?

  • AI-powered auto-coding feature automatically organizes data into themes the software identifies

Free Trial: 14-day free trial

Pricing: NVivo licenses range from $1,019 to $2,038 depending on the use case (academic, government, commercial). But if you’re a student, you can get a special price of $118

User review: “I think this software is great for beginners in qualitative research. But in terms of value for money, I think this software doesn’t come with the best offer.”

Rating on G2: 4.1 stars ⭐⭐⭐⭐

5. ATLAS.ti

About the product: ATLAS.ti is a powerful qualitative data analysis software that integrates AI-driven tools to support thematic analysis. It’s another classic academic tool available for many university students and professors.

How is AI used in Atlas.ti?

  • AI chatbot that allows users to query, clarify, and extract key information from documents using an intelligent AI chatbot
  • AI Coding feature uses the GPT model from OpenAI to automate coding, identify essential insights, or suggest new lines of research inquiry
  • Text Search tool uses AI to look for more relevant segments of data quickly and with less effort

Free Trial: 5 days of use over a 45 day period (yes, it’s a bit weird)

Pricing: Highly variable, ranging from $50 - $9,300 depending on who you are and how long you need access for

User review:The software is intuitive and adaptable to the researcher; I've been using it since 2014 and wouldn't switch to any other choice. Initially developed for grounded theory, the software is not limited to other qualitative analyses. A lot depends on the researchers and their research design.”

Rating on G2: 4.7 stars ⭐⭐⭐⭐⭐

AI Thematic Analysis: Free Tools

While there are many options for AI thematic analysis, the free ones are largely limited to AI chatbots like ChatGPT and Claude.AI.

If you want a tool that truly integrates AI into your thematic analysis workflow, allowing coding and careful analysis, you should turn to options like Looppanel, NVivo, or Atlas.ti.

Ethical considerations with AI thematic analysis

While new technology like AI is game-changing in terms of efficiency, it’s important to keep in mind the other side of the coin. When using AI for thematic analysis, there are several ethical considerations and safeguards to keep in mind:

1. Data Privacy and Security

  • Make sure you obtain the data you're analyzing with proper consent and in compliance with relevant data protection regulations (like GDPR or HIPAA). You don't want to be caught on the wrong side of the law!
  • Implement robust security measures to prevent unauthorized access, data breaches, or misuse of sensitive information.

2. Bias and Fairness

  • Be aware of potential biases lurking in the AI algorithms and training data that may lead to skewed or discriminatory results. We want our analysis to be fair and square!
  • Regularly assess and mitigate algorithmic bias to ensure fair and unbiased analysis across different demographic groups. Everyone deserves equal treatment.

3. Transparency and Explainability

  • Maintain transparency about the use of AI in the thematic analysis process and communicate it clearly to stakeholders.

4. Human Oversight and Accountability

  • Ensure that AI-generated insights are reviewed and validated by human researchers with domain expertise. We can't let the machines run the show entirely!
  • Use AI as a tool to augment human analysis, not as a complete replacement for human judgment. Collaboration is key!

5. Data Quality and Representativeness

  • Ensure that the data used for AI analysis is accurate, complete, and representative of the target population. Garbage in, garbage out, as they say.
  • Regularly assess and address any data quality issues or gaps that may impact the validity of AI-generated insights. We want our findings to be rock-solid.

6. Informed Consent and Participant Rights

  • Obtain informed consent from participants whose data will be analyzed using AI, disclosing the use of AI and its potential implications. Honesty is the best policy.
  • Respect participants' rights to privacy, data ownership, and the ability to withdraw consent if desired.

By keeping these ethical considerations and safeguards in mind, researchers can harness the power of AI for thematic analysis while ensuring responsible, fair, and trustworthy practices that respect the rights and well-being of all stakeholders involved. It's a win-win situation!

And there you have it! The best AI thematic analysis tools to speed up your research and lessen the number of headaches you get from squinting at a code-book.

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