ONLINE WEBINAR : Saving Analysis Time with GenAI – Myth or Reality? [Feb 27, 2025]

If your or your team’s job involves spent hours sorting through transcripts, notes and raw open-ended data, you must have wondered if there’s a faster way to do things. This webinar was designed to address this question, often thrown up by the Qualitative Research community we work closely with and for.

flowres.io did a deep dive into how Generative AI (GenAI) can help researchers save time, automate tedious tasks and focus more on insights rather than manual grunt work.

Spoiler alert! AI can do a lot, but it needs human oversight to shape a compelling data narrative.

To start with… what do we actually mean by “Saving Time”?

Let’s be honest – the term “time-saving” gets thrown around a lot, but what does it really mean in research? We broke it down to three big wins:

1.      Less repetitive work – Automating sorting, tagging, and data structuring.

2.      Fast & accurate verification – Quickly finding and cross-checking insights without endless scrolling.

3.      Seamless handling of multiple reference points – No need to toggle among a million documents, Excel sheets, and notes.

Next, we recapped Research struggles we know all too well

Before jumping into AI solutions, we highlighted pain points every researcher can relate to:

·         Sorting through mountains of data – Finding what matters in long interviews or focus groups.

·         Verifying insights – Making sure what we think we heard is actually what was said.

·         Toggling among sources – Taking away the exhaustion of jumping among multiple transcripts, to compare and contrast findings

·         Summarizing key findings – Turning pages of text or reams of slides, into something digestible for clients or stakeholders.

·         Building reports that tell a story – Not just presenting “Here’s what they said”. Instead, crafting a compelling narrative.

Okay, so how does GenAI solve these pain-points?

We walked attendees through some game-changing ways GenAI can streamline the Qualitative Data analysis process:

1. Thematic Analysis on Autopilot

• AI can read multiple transcripts and pull out key themes in seconds. Imagine what that means, for a large-sized Qualitative study involving tens of transcripts!
• It helps avoid reading fatigue – no need to manually highlight everything relevant to your research objectives.
• It can contextualize moderator inputs yet focus on what respondents actually said.

2. Data Sorting Without the Headache

• AI can categorize responses and organize data into grids, if grids is what you’re more comfortable working from.
• No more manually copy-pasting into and formatting Excel for hours!
• Works great for segmenting by demographics eg. age, gender, location.

3. Comparing Segments Without Losing Your Mind

• Want to see how men vs. women feel about a topic? AI can sort it out for you and present it to you in a convenient, easy read.
• Helps uncover hidden insights that might be missed with manual analysis. Those outlier responses can now get a voice, with the right kind of prompts.

4. Finding and Verifying Quotes Easily

• AI automatically extracts relevant quotes linked to key insights.
• Saves time digging through transcripts to find that one perfect supporting statement.

5. Making Research Notes More Useful

• AI can ingest structured research notes and analyze them – no need to wait for full transcripts.
• Ideal for fast turnaround projects, where insights are needed super-quick. Or for iterative, concept/product development studies; where respondent opinions are required on minor tweaks made to concepts/products.

But wait… what about AI mistakes?

Yes, AI isn’t perfect (and nobody claimed it was). There’s always a risk of:
⚠️ Misinterpretation – AI might summarize things wrong or overstate findings.
⚠️ Out-of-context insights – Some details can get lost in AI’s simplification process.
⚠️ AI “hallucinations” – Sometimes, AI makes up information that wasn’t in the original transcript

Solution? Always double-check AI-generated insights against raw data. AI is a helper, not a replacement for human judgment.

So, is it worth infusing GenAI into my QDA workflow?

Absolutely! AI won’t replace researchers, but it does make their lives easier. The biggest takeaway from this session?
✅ GenAI is great for automation, but human researchers are still required, to guide the storytelling.
✅ GenAI saves hours doing tedious tasks – so researchers can focus on the actual insights.
✅ The key is balancing AI efficiency with human intuition.

Want to explore GenAI in your Qualitative Data Analysis process? Start experimenting with purpose-built, AI-driven flowres and see how GenAI can become an efficient research sidekick.