The impact of AI on UX Researchers and Agencies
AI is heading our way, and whether you like it or not, if you are a design researcher, it will impact the way you work. To me, the opportunities far out way any fears you may have and here is a summary of the reasons why.
The impact on researchers
A range of things will be changing as AI becomes a tool we us on a daily basis, in the same way we already use transcription tools. There is some way to go before a researcher can create an AI version of themselves and moderate multiple parallel research sessions using a script also created by AI. That power won’t be at our fingertips for some time, even if Eminem’s fanbase is already benefiting!
But progressively, in the same way we now use transcription, things are going to change. Let’s break it down by activities that form part of the role.
Creating recruitment screeners is going to become less of a chore and gain in greater accuracy. AI will have the ability to create question patterns that deliver the perfect screener in far less time than we can.
Scheduling participants will be completely automated. The discussion over availability, organisation of the most efficient schedule will all be done by AI. It will also be able to identify fraudulent participants ahead of the research, cancel and replace them.
Discussion Guide Creation will go the same way as screeners. We can already ask ChatGPT to create a set of non-leading interview questions to explore a subject and the results are pretty good. This will only get better. AI could even be used to dynamically improve the discussion guide based on the data being captured, reacting to a particular participant style or following the direction a conversation goes in.
Analysis of audio-video and transcription is an obvious area where AI can save time. This area in particular will free researchers to spend their time where it adds most value in answering the “so what” question, making recommendations and working with designers and product owners more strategically.
Quantitative research (surveys) may be designed by AI, and similar to screeners the logic and cross-referencing will be more accurate and effective. We will also stop worrying about the exponential analysis time associated with verbatim answers. AI will allow us to analysis vast amounts of data far more quickly, which in turn will enable us to be more creative with our research design.
Unmoderated research will be transformed. Right now, too many organisations make critical business decisions based on flawed insight. The primary cause of this is unskilled people creating poor profiling questions and leading tasks/questions. Platforms like Usertesting.com have exploded organisations capability to carry out research but AI will allow for the delivery of accurate insight.
Research outputs may be machine generated so that researchers are stepping far further into the design process than they have previously. This will create even greater collaboration with designers and developers.
Researchers will need to understand AI. The products and services we work with will feature AI in ways we haven’t yet encountered. And also, ways end-users and customers haven’t experienced. Researchers will need to help organizations understand how to deliver meaningful customer experiences using AI. There will be governance issues, privacy issues and much more that will impact not only a customer experience but their relationship with a brand. Researchers will be entrusted with answering these questions and will need to understand AI to do so.
The impact on agencies
Agencies may be fearful that brands will no longer need them. I think there is no doubt that AI will make their internal researchers more efficient and able to deal with far more work. And perhaps some organizations will see AI as a way to save money on the research they are doing.
However, in my experience, organizations that do research as part of the product development cycle, always want to do more. They are limited by three things:
- Budget
- Time
- Resource capacity
AI will remove these barriers. By enabling researchers to do more research an organizations budget will go further and there will be more capacity. Individual projects will be completed more quickly so that research can fit into product development timelines that previously would not allow it.
Brands I speak to would love to do more discovery or generative research, but don’t have the budget or resource to do more. If they are doing evaluative research, they would also do more if the project timeline wasn’t slowed up so much. Product owners wouldn’t be asking designers to run research if the organisation had more capacity.
For the time-being at least, researchers will still be needed. To ask AI the right questions, know what good looks like, make the strategic choices.
What AI is ultimately doing is increasing the markets capacity to do research. That has been going on for twenty years — just look at the rise in population of researchers. There are more researchers because more research is being done. Even after all the recent tech layoffs, which included researchers, we all know that in 12 months’ time, they will all be fully employed again.
Agencies will need to embrace AI and build on the efficiencies available. This won’t be about access to technology. It will be about people, organisational change and innovation. That is what agencies already do and a key reason why brands work with them. The other is overflow capacity and that will remain the case as brands grapple with the impact on their own organisation.
What next?
My challenge is to get involved and start learning about AI if you have not already done so. This isn’t a fad. It’s not augmented and virtual reality. There will be rapid innovation, lots of mistakes, lots of learning but don’t let it pass you by.
