AI Can Make Market Research Faster. But Can It Really Tell Us What People Think?

Where AI Market Research Can Add Value

Artificial Intelligence is rapidly changing the way research is conducted. Used well, AI can save researchers considerable time, helping us process large volumes of information, identify patterns within datasets, summarise existing evidence and support some of the more labour-intensive stages of analysis. These benefits are real and, as researchers, we should embrace them. However, there is an important distinction between using AI to support research and allowing it to become a substitute for research itself. 

Research has always involved necessary but time-consuming tasks. Reviewing qualitative data, organising themes, interrogating datasets and searching existing evidence all require significant researcher time. AI can accelerate some of these processes, creating an opportunity for experienced researchers to spend more time where human judgement adds greatest value: questioning, interpreting, challenging and understanding what the evidence actually means. 

AI as a Research Thinking Partner

AI can also be a useful thinking partner. It can suggest alternative hypotheses, identify gaps in questioning, interrogate assumptions and offer different ways of approaching a research problem. But the important word here is suggest. AI-generated outputs should be something researchers interrogate, rather than simply accept. 

The temptation with increasingly sophisticated AI is to assume that because an answer sounds convincing, it must be correct. Good researchers know the danger of doing this. We question evidence, look for contradictions, consider what might be missing and test whether apparently straightforward findings withstand scrutiny. The same principles must apply to AI. If it identifies a pattern, we should ask why. If it produces an interpretation, we should examine the evidence behind it. If it summarises qualitative data, we should consider what nuance may have been lost. 

The Limits of Synthetic Respondents

There is also growing interest in synthetic respondents, AI-generated personas and bot-generated research data. The attraction is understandable. Recruiting participants, conducting interviews and gathering survey responses takes time and money; an artificially generated audience can produce hundreds of plausible responses in moments. 

Synthetic data may have a useful role in developing hypotheses, exploring scenarios or identifying questions for further investigation. But modelling how somebody might respond is fundamentally different from asking a real person about an experience they have actually had. 

Why Human Behaviour Is Hard to Replicate

Human attitudes and behaviours are rarely neat. People contradict themselves. What they say they value can rapidly change according to experiences. Their views are influenced by context, emotion, memory, culture and individual circumstances. Sometimes the most valuable research finding is precisely the one nobody expected to find. If we rely on models trained on what is already known, we risk reproducing existing assumptions rather than discovering something new. 

Using AI Responsibly at Mackman Research

At Mackman Research, we are not resistant to AI. Quite the opposite. We actively support responsible AI practices and continue to explore how the technology can be used effectively, ethically and transparently within our work. For us, the important question is not whether researchers should use AI, but where it genuinely adds value and where human judgement, curiosity and intervention remain essential. 

That commitment to using AI responsibly does not diminish our commitment to human research. Our researchers continue to focus on real human experiences, interpreting not only what people tell us but also the context, contradictions and meaning behind their responses. Technology can help us process information, identify patterns and challenge our thinking, but it cannot replace the value of listening to people and understanding their experiences first-hand. 

Keeping Human Experience at the Centre

AI can help us work faster, challenge our thinking and interrogate information in new ways. But insight ultimately needs to help organisations understand people and make better decisions. At Mackman Research, our role remains to bring those two things together: using technology intelligently while keeping human experience at the centre and guiding our clients from robust insight through to informed strategy.