“Why did you get into AI?” If I had a dollar for every time someone asked me this question, I’d be a millionaire by now. Well, maybe not a millionaire, but I’d have a decent stash of pocket change.
The truth is, my journey into AI in qualitative research hasn’t been linear or straightforward. After attending QRCA 2025, I realized that many qualitative researchers are on a similar journey—one filled with ups and downs, curiosity, and skepticism.
AI in Qualitative Research: Transforming the Landscape
I haven’t always been optimistic about AI in qualitative research. As an anthropologist, I initially had my hesitations and reservations. But instead of resisting change, I chose to explore it. Since late 2022, I’ve been actively delving deeper, experimenting, and pushing the limits of AI in qualitative research.
Over time, I became more than just an AI enthusiast; I became bullish. So much so that I co-founded Qualz.ai, an AI-powered platform designed for qualitative researchers. Mind the key word here—researchers.
Yet, even with my deep immersion in AI in qualitative research, QRCA 2025 was a wake-up call.
But even with my deep immersion in AI, QRCA 2025 was a wake-up call.
I’ve always known that qualitative research is at the heart of market research, but I had never met so many independent qualitative researchers in one place—people who live and breathe this work. For me, QRCA 2025 wasn’t just a conference—it was my initiation into a community I had long observed from a distance.
I was excited but also wary. For 3.5 days (thanks to the Philadelphia Eagles’ Super Bowl victory parade for cutting the last day short!), I engaged in deep conversations with researchers from the U.S., Canada, the UK, Australia, and beyond. We discussed AI—its promises, its pitfalls, and its place in our field.
What I found was a mix of curiosity, excitement, hesitation, and uncertainty—but above all, a realization: AI is no longer a future discussion. It’s a present reality.
The AI Conversation: A Crossroads for Qualitative Research
When it comes to AI in qualitative research, everyone had an opinion—and no two perspectives were the same.
Some were excited and eager to learn and experiment.
Some were concerned, unsure of what AI means for their careers.
Some were caught in FOMO (fear of missing out)—aware that AI is advancing but unsure where to start.
But this year, the conversation felt different. It wasn’t just about AI as a tool—it was about AI as a transformation.
There was a universal awareness among researchers that AI will drastically change the qualitative research landscape—whether they embrace it or not. Some feared this meant a shift away from traditional methodologies, a loss of the depth and nuance that qualitative research is known for. Others saw AI as an inevitable force, one that could expand the scale, speed, and accessibility of insights in ways we’ve never seen before.
But all of them knew one thing for certain:
AI will redefine how qualitative research is conducted, if it has’t already started, and there is no turning back.
However, with this realization came three major concerns:
Uncertainty – What can AI actually do for qualitative research? What are its limitations?
Fear of Missing Out (FOMO) – Am I falling behind if I’m not using AI? How do I catch up?
Too Many Choices – With so many AI tools flooding the market, which ones are worth using?
As I spoke with researchers, I noticed that most fit into three distinct categories based on their relationship with AI.
Through conversations with researchers at the conference, I noticed three distinct perspectives on AI in qualitative research:
1. The Concerned: Cautious but Open-Minded
These researchers haven’t actively used AI in their work-—their knowledge comes mostly from hearsay, news, and speculation.
Their biggest concerns?
Will AI replace human researchers?
Will AI dilute the depth of qualitative insights?
What does AI mean for my career?
But what struck me was that they weren’t anti-AI. They weren’t afraid of it—they were concerned about the unknown.
2. The Researchers on the Fence: Experimenting but Unsure
These researchers had some exposure to AI tools—perhaps they had used AI for transcription, coding, or basic analysis. But that’s where their journey stopped.
Their biggest questions?
How do I integrate AI effectively into my workflow?
Which AI tools are genuinely useful for qualitative research?
How do I keep up with AI without it becoming overwhelming?
3. The AI Embracers: Adapting and Leading
This group has already incorporated AI into their research methodologies and actively seeks ways to optimize its use.
They weren’t asking, “Should I use AI?” They were asking, “How can I make it work better?”
They understand that:
AI is here to stay.
AI won’t replace qualitative researchers—it will amplify their impact.
Adaptation is the key to thriving in the AI era.
Instead of resisting, they were learning, experimenting, and optimizing.
A Shared Realization: AI Isn’t a Choice Anymore
One thing became crystal clear at QRCA 2025:
AI in qualitative research is not a question of “if”—it’s a question of “how.”
Regardless of where someone stood on the AI spectrum—whether concerned, on the fence, or fully embracing AI—there was optimism.
Why? Because deep down, everyone recognized one fundamental truth:
AI will be a part of everything we do in the near future—not just in research but in every field.
There are uncertainties, yes. There are challenges.
Ignoring AI is not an option.
We Don’t Know What We Don’t Know—So Let’s Learn
I get it. AI can feel overwhelming. It’s new, evolving at breakneck speed, and often misunderstood.
But here’s my argument:
- The only way to truly understand AI’s role in qualitative research is to use it.
- We can debate, theorize, and analyze AI from the sidelines, but until we get our hands dirty, we won’t know its real strengths and weaknesses.
- So let’s explore. Let’s test. Let’s learn.
- Staying in denial won’t stop AI from advancing—but embracing it can help us shape its future.
Final Thoughts
To my fellow qualitative researchers: Let’s embrace AI—not blindly, but thoughtfully. Let’s shape it, refine it, and use it to make our work more powerful than ever.
If you’re navigating AI in qualitative research, I’d love to connect.
Visit Qualz.ai to see how we’re helping qualitative researchers harness AI responsibly.