Introduction
Introduction: How has artificial intelligence changed the life of a UX researcher?
The initial entry of artificial intelligence into the day of any UX researcher was usually nice and simple… like asking, "Correct my grammar before I send the email."
But over time, artificial intelligence has become more than just a linguistic assistant. It is now present in every application, every service, every product, and every user journey — from subscribing to an internet company to communicating with customer service.
For a user experience researcher, the pressure now is not "Should I use AI?" but rather "Can I even work without it?".
At Flipdish, the experience has become completely different: artificial intelligence does not do the work instead of the researcher, but it has become an additional engine that stands behind you, lifting you a step above the chaos and giving you a speed that was previously impossible.
This article takes you on a journey through four main stages in the work of a UX researcher with AI — planning, analysis, Dovetail management, and reporting — and then concludes with the most important lesson in the story: how to stay on the side of the user without allowing artificial intelligence to become an echo chamber.
1) Planning: How does AI help you build a research plan without confusion?
A good researcher is a good planner.
And planning usually takes time… a lot of it.
Before an interview, workshop, or project analysis, the researcher needs to map out the path before they start walking.
This is precisely where artificial intelligence shines.
At Flipdish, before any task:
ChatGPT or Gemini is given the context of the project
and then asked to build a clear action plan
that includes steps, risks, tools, and alternatives.
The nice thing is that Gemini tends to be more "empathetic" in its approach, while ChatGPT is more "structural" and rigorous.
Having both is like having consultants: one gives you depth, and the other gives you structure.
With the introduction of automation tools like Zapier, AI has started to help the researcher in areas beyond planning:
Automatically connect Dovetail with Notion, update databases, and facilitate the product team's access to real-time insights.
Sometimes the solution is 10 steps in our imagination, while Gemini suggests one step that does the same job... better.
2) Analysis: Can AI analyse qualitative data? Yes... with conditions.
This area is sensitive.
Interview analysis, understanding the user's voice, extracting patterns...
This is the essence of a UX researcher's role, and any attempt to fully replace it with AI could kill the spirit of research.
But AI here does not replace the researcher — it extends them.
At Flipdish, what is called a Gem is created: an 'intelligent' version of the researcher, trained on:
The researcher's analytical style
The context of the company and customers
Previous research
Personas and Archetypes
Strict ethical guidelines that data should not be used to train the system
And this version is not used for every project; rather, each project gets a customised Gem so that the analysis does not lose its true voice.
How does AI assist in analysis?
Writing accurate summaries of interviews
Extracting insights with timestamps from the interview
Suggesting patterns and notes
Generating a comprehensive Tags board (very useful in Dovetail)
But more importantly:
AI does not produce a ready-made report.
Rather, it produces a reference map to help the researcher return to the moment, the tone, the emotions, the user's voice itself.
And this alone saves days of work.
Read the article for importance and further information: AI for designers: How to double your speed and quality in UI/UX with smart tools
3) Dovetail: AI enhances engagement, not just analysis.
Dovetail adds more AI tools with every update.
But its strength is not deep analysis — it’s team collaboration.
The feature “Chat with your research” has become a game changer:
Instead of the designer or product manager reading 40 pages of a report, they ask a simple question:
“Why do users close the page at Step 3?”
And they get the answer directly from interviews and recordings.
In this way, AI not only helps the researcher… but helps the team understand and trust the value of research.
4) Presenting results: How does AI turn heavy UX reports into engaging interactive dashboards?
Long reports are usually not read.
Even if they are amazing and full of Eureka Moments… they remain trapped in the inbox.
And this is where AI comes into play:
Figma Make
Bolt AI
v0 from Vercel
Cursor
You can throw your report into Figma Make, and it outputs a sleek interactive dashboard that you can send to the whole company.
This alone boosts engagement from marketing, sales, and support departments… who usually don’t have time to read in-depth reports.
The result?
Research transforms from PDF to a live experience.
5) The red line: What is the boundary so we don’t become “prisoners of AI”?
In a recent project, the researcher built a Custom GPT containing Personas, Archetypes, and previous research findings.
The idea was brilliant: making research more usable across the company.
But there was a comment from the Product Manager:
“The idea is nice… but aren’t we afraid this becomes a substitute for the real user?
AI could turn into an echo chamber and give us aggregated and unrealistic opinions.”
And he was absolutely right.
Artificial intelligence is a great tool, but it doesn't always reflect the user's real life.
Therefore, controls have been tightened, and everything has been reset.
The golden summary:
AI is excellent… as long as it strengthens your relationship with the user, not cuts it.
The big takeaway: artificial intelligence will not steal the researcher's job — it will amplify it.
Today's artificial intelligence is not the 'smart assistant' that works instead of the researcher.
It is:
A facilitator
An organiser
A memory expander
A time saver
And a closer voice of the user for the whole team.
But in the end, decisions, interpretations, and human sensibility — all require a real researcher.
Artificial intelligence elevates you… but it cannot be you.
And that is the value that will define the future of UX Research in the coming years.
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