A panel of junior researchers at the MRS Annual Conference reflected on the benefits and drawbacks of AI and its impact on the fledgling careers of those entering the industry.

While they raised a plethora of views, citing many pros, and some cons, there was emphatic agreement on one point: AI in market research is nothing without traditional analytical nous.

Chair Rebekah Smith, research manager at Firefish UK, said: “With an industry in flux, what does is mean for us who are planning our careers; how are we experiencing those changes in our day to day roles; what do we think the skills of tomorrow are; and what do we want to do to future proof ourselves in the industry that we love?”

Joining her were a five-strong panel: Adrianna Magnetti, research manager, Firefish UK; Fenella Twohig, strategist at The Pineapple Lounge; Coco Ravan, research manager, Magenta; Olivia Radcliffe, research manager at Simpson Carpenter; and David Walmsley, digital insight manager at Holland & Barrett.

Ravan kicked things off, explaining how when she entered the industry, basic aspects of research were explained painstakingly: this is what an interview is, this is what a focus group is, this is when you favour one over the other, etc.

“There was really that focus on training, there were human layers and human feedback, and that, for me, was so important – the friction of improving and getting better,” she said.

Ravan added: “I just don't know if there’s that same focus now between researchers, because so much of it is AI-focused. Where does that leave room for skills development for those junior researchers, and is the adoption of AI unintentionally creating a skills gap?”

On the other hand, Radcliffe was an advocate for how AI has expanded possibilities, while acknowledging that it’s human judgement that “decides what’s powerful”.

“For young researchers coming into the industry, AI can be quite seductive. It can creates things that sound very polished, neatly packaged, quite convincing. In a way, it’s highlighting that we have to be even more intentional, to hone those critical thinking skills,” she said. “Developing your voice as a young researcher is one of the most important skills that you learn.”

She sees the value in using AI as a “sparring partner”, to stress-test the different ways of expressing an insight.

“You can say something in 10 different ways, but one word can have a huge impact on the way that lands,” she said.

However, Walmsley, speaking from a client perspective, issued a warning not to be over-enamoured with or over-reliant on the shiny and new.

“The thing that scares me the most from the client side is that I'm seeing people use data or research without their traditional skills. That’s the really scary part, because they don't know what good looks like, they don't know how to spot the errors.

"The AIs are really good at sounding smart, sounding really confident. But they hate saying: ‘I don't know’.”

Magnetti, whose role at Firefish is almost exclusively AI-focused, reinforced his argument, explaining how a junior learning critical thinking skills is vital to good research.

“Previously, I learned how to analyse data through brainstorming, analysis sessions, I had managers who told me how to look at the data and spot the connection the behaviours and the nitty-gritty.

“I think that for a young researcher, if they don't have that skill, it will be really hard in the future to actually question AI and be critical.”