Tom Woodnutt
Tom Woodnutt is Founder of Feeling Mutual, the multi-award winning agile online qualitative research specialists. He helps clients and agencies run global studies and offers training in the space. Tom has been a Digital Skills trainer for the Association of Qualitative Researchers (AQR) and is a regular speaker at industry conferences, including the MRS, MRMW and IleX.
There are a few ways that I think independent qual researchers are well placed to benefit from the changes that AI will bring to the qualitative research industry - this comes down to the agility independents have and a probable new wave of qual research done by non-expert researchers that they can help elevate and deliver.
Is AI a threat or an opportunity for independents?
Indies can ride the wave of DIY qual
AI makes it easier for non-experts to design, run and analyse qual research. So AI innovation that supports DIY qual is likely to pull in new entrants from diverse worlds of management consultancy, design, through to innovation and advertising as well and more hands-on, in-house client research teams.
This trend will also be driven by the commercial pressure for consultancies to swim further upstream and get more control over strategy - which is something that delivering qual research can help with as it feeds directly into decision making.
Independents have the agility and ability to ride this new wave of cheaper, faster and perhaps more straightforward qual projects fueled by AI. That’s because this new wave of lower priced, more straightforward work, will quickly reveal the need for expertise. As people who do research but aren’t experts realise how specialist knowledge of how to design, run and interpret projects effectively will quickly elevate the value of the work.
Indies can fill the knowledge gap
Qual can easily go wrong if it's designed wrong; for example by underestimating the time it takes to have discussions, the incentives required to encourage people to participate, designing a study with the wrong people or testing ideas in ways that corrupts the validity of the finding. Also the task of reporting is very challenging when there's so many competing interpretations available from the data. So this new wave of AI powered DIY qual will quickly reveal a gap for experts to manage some or all of the process - and this gap can be easily plugged by independent qual researchers who are willing to offer elements of a service (for example design or moderation or analysis). These gaps are less likely to be filled by full service research agencies as it is in conflict with their business models.
I’m not saying there will be a race to the bottom with all qual projects becoming simpler, cheaper and more AI reliant. I'm envisaging multiple races on different tracks of complexity, speed and budget - with lighter more AI reliant simple projects co-existing alongside more manual, nuanced, complex and human led, bigger budgeted approaches.
Democratisation is inevitable but not bad news for indies
This is not a new dynamic and it’s something we’ve seen in many other sectors - you only have to look at web design which has seen DIY / cheaper / less tailored websites built by tech like Wix and Wordpress living alongside more bespoke, expensive websites built by experts. The same may happen in qualitative research - broadly speaking two different levels of depth, nuance and tailoring - one more reliant on AI, faster and more affordable, and the other more manual, requiring more investment offering more tailored, nuanced and deep qual.
As long as independents can get their hands on AI tools and learn how to use them effectively, their value in the ecsoystem will become even more in demand.
