The Campaign for Real Qual: Four Provocations in an AI-Driven Era

We are passionate about qualitative research. We want better qualitative research practices, techniques, capabilities and results. But we are also realists. The last few years have seen an explosion of AI driven tools, platforms and practices that are creating debate and change in the broad market research world. So, it would have been remiss of us to not think about the impact on qual.

Dave has been using and advocating AI platforms built for market research for a decade. Craig has been exploring their potential ever since the GPT revolution of 2022. Earlier this year Craig initiated a broad look at the tools and the impact of AI on qual with his Campaign for Real Qual. A few months of writing articles, seeking out opinions and provocations has resulted in an initial e-book.

So, what have we learned?

A lot - but here are four recurring thoughts as AI continues to reshape qualitative research:

1. Are We Losing the Craft of Qual?

The explosion of AI platforms is both energizing and overwhelming. Every week, new tools promise faster, more scalable research. But along the way, we risk losing something important – the craft of qualitative research. At its best, qualitative research is not just a method, it’s an art, a way of seeing and a discipline of deep human understanding. It helps uncover what is hidden from view – the social and cultural forces that shape whether brands deeply connect with people.

Great qualitative work is heavily reliant on the practitioner’s skill to forge deep human connections, their intuition to make meaning from what they are seeing, hearing and feeling and their ability to craft a compelling, commercially relevant narrative. Little things, a wink between respondents, a tone of voice, sarcasm, the shifting of feet. 

These are not inefficiencies to be eliminated – they are the core of what makes qual different from quant. Prioritising speed and scale risks losing depth and nuance. The Campaign for Real Qual emerged partly in response to this – a call to pause, reflect and protect the things that make qual powerful – not by rejecting AI, but asking how we can use it without bypassing the craft – or ignoring the trade-offs.

2. Friend or Foe? AI's Uneasy Relationship with Qualitative Research

AI is fascinating: fast, scalable, and increasingly capable. But it’s also alien to the human dynamics that underpin great qual work. It can summarise, synthesise, even simulate – but so far it doesn’t build rapport, adapt on the fly, or sense what’s unsaid. It lacks human instinct. 

AI as friend or a foe to qual? Well, it depends on who’s driving the relationship. Used carefully, it can free up time, build on and challenge your own ideas, and give you new, creative ways to land insights. But used blindly, it flattens everything it touches. The problem isn’t AI itself, it’s the assumption that AI knows how qual works. It doesn’t. That’s our job.  

So, what we have found is needed is critical engagement. Use it, experiment, try different AI offerings and cross check output, then look how to add value.

3. Do We Need to Rethink What Qual Is?

Let’s go one step further. What if the emergence of AI doesn’t just challenge how we do qual — but what qual even is?

We’ve observed increased demand for ‘qual at scale’ – platforms delivering hundreds of AI-moderated interviews quickly. We understand the appeal and can see when it would be useful. But it also feels like quant in qual’s clothing. 

What’s at risk here isn’t just technique – it’s meaning. When qual is reduced to transcripts and sentiment scores, we lose the richness of human connection – the body language, the silences, contradictions, ambiguities - the fringes of human experience where insight lives.

We are seeing some of the qual community turning to deeper, often part forgotten anthropology-based ideas to reinvigorate qual and that can only be a good thing. 

4. A Qual Researcher’s Guide to Staying Relevant

If all of this sounds critical – it’s because we care. The Campaign isn’t a rejection of change. It’s an invitation to engage with it intentionally. 

So how should qual researchers adapt:

1. Experiment. Don’t just watch from the sidelines. Try the tools. Stress-test them. See where they help — and where they don’t. Share generously.

2. Sharpen your human skills. The things AI can’t do – empathy, intuition, sensemaking – are now your superpowers. Lean into them.

3. Keep your original voice. Clients still buy from people who offer a strong narrative, clarity and confidence. AI can generate language, but it can’t tell stories that matter. That’s still your role.

The future isn’t about choosing between AI and human insight. It’s about understanding the role of each and being honest about the trade-offs.

And we’re just getting started.

The Campaign for Real Qual is still unfolding – through writing, conversation and experimentation. If you’re navigating similar questions, we invite you to join us:

Access the free eBook, custom GPT & podcast

Join our LinkedIn group AI Experiments in Qual