I will preface this by saying I am old enough – despite looking about 12 – to remember the rise of online surveys, the ‘death’ of face-to-face qual (remember that, after COVID) and ‘Big Data Will Take Your Job’ chat. New tools and approaches emerge all the time and that is something to be celebrated – it pushes us forward.
Used well, AI can save time. It can help with admin. It can help sort, sift, tag and summarise. And yes, there are probably some types of research where large-scale AI moderation is good enough. If you want to test how people use laundry detergent or washing-up liquid at scale, fine. And more broadly, if the task is functional, low stakes, repetitive and mostly about quick reaction, I can see the case for it.
But…there are some conversations that should not be handed over to AI.
I mean proper qualitative conversations. The sort where the value is not just in getting an answer, but in how that answer is reached. Those where what matters is not just the words someone says, but the pause before them, the wobble in their voice, and the fact they nearly do not say it at all.
These topics are quite different on the surface, but they share a common thread. Each one touches on emotion, vulnerability, memory, identity, and care. They are not things that can be rushed or treated mechanically. They need space, thoughtful judgement, and a little humanity.
AI does not have emotions. It does not understand what it means when someone laughs at the wrong moment because they are trying not to cry. It does not know when to sit in silence for a second longer. It does not feel the shift in a conversation when someone has decided they trust you enough to say the thing they had not planned to say.
In sensitive or emotional research, moderation is not just a delivery mechanism for questions, nor a neutral pipe through which data passes. A good moderator is actively listening, making decisions in real time, weighing what to probe, what to leave alone, what to come back to later, when to soften, when to stop. Crucially, a good moderator understands when to recognise that the most important thing in the room is not the discussion guide.
Sometimes the most useful moment in an interview is not a clean answer to a neatly phrased question. It is the messy, sideways bit. The moment where someone goes off track and tells you about the first time they felt seen. Or the point where they stop talking about a museum display and start talking about their dad. Or when what looks on paper like a rational decision turns out to be tied up with fear, grief, shame or pride.
There is also an ethical point here. When people are talking about self-harm, suicide, trauma, illness or grief, they are not just giving you content. They are giving you something of themselves. The least we can do is meet that with care, competence and human presence. Not because humans are perfect (there are so many examples currently of how we are not) – but because care in those moments is not a nice extra. It is part of the work. And yes it costs time, and yes it costs money.
The same applies, in a different way, to cultural research. It might sound less obviously serious than health or mental health research, but emotional connection still matters. When someone explains why a place, an object or a story means something to them, that is not trivial. It can be bound up with identity, family, belonging, loss, memory, aspiration. If you are trying to understand that well, you need more than a system that can ask the next question. You need someone who can recognise feeling and respond to it.
None of this means AI has no place in qualitative research. I am not anti-AI and it is absolutely a part of the toolkit. It can help researchers do their jobs better by reducing time spent on laborious tasks, supporting analysis and helping to manage scale where the subject matter allows for it.
But support is not the same as replacement. There is a difference between using AI as a tool and asking it to do the human bit in projects that require the human bit.
My concern is that that distinction is getting lost in the rush to automate.
By definition many of the clients who focus on the most sensitive subject matters are also the ones with the largest budget constraints – charities, CICs, etc – and the AI approach is potentially an attractive one from a financial perspective.
There is a temptation to assume that if an AI can produce plausible follow-up questions and keep a conversation going, it can moderate. But plausible is not the same as good. And good is not the same as safe. A conversation can look fluent and still be shallow. It can sound responsive and still miss the point entirely.
And that is the risk. Not just that AI moderation will be clunky or imperfect, but that it will be convincing enough for people to think it is doing something it is not. It might gather words. It will probably gather lots of them. But it may still fail to recognise what those words actually mean in human terms.
So yes, use AI where it makes sense. Use it to speed up the repetitive bits. Use it to help process scale. Use it to test the washing up liquids.
But there are some conversations worth having properly – and I suspect there always will be.
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