The insight industry has a PR problem

Recently, we had two very different client conversations.

One client told us:

"We don't need the analysis. Just do the research and give us the transcripts. We'll use AI to find the insights."

Another told us:

"Please don't use AI. We're paying for your thinking."

Two completely opposing positions, yet both expose a question our industry has never properly answered: What exactly are clients paying researchers for?

For years, we've done a brilliant job of explaining the importance of listening to customers. We've talked about customer centricity, democratising insight and bringing the consumer voice into the room. But I wonder if we've accidentally created our own PR problem.

Too often, researchers are seen as the people who gather customer opinions rather than the people who turn those opinions into understanding.

I've seen this throughout my career. In many organisations, strategists, consultants and branding specialists are viewed as the thinkers. Researchers are viewed as the evidence gatherers.

The irony is that anyone who has spent time doing qualitative research knows customers don't hand us insights. They give us stories, experiences, contradictions and opinions. The insight comes from interpretation. That's why I find the AI debate so interesting.

If you believe the value of qualitative research lies in collecting customer feedback, then AI analysis feels like a natural next step. But if you believe the value lies in understanding what those conversations actually mean, then the discussion becomes very different.

Because transcripts aren't insights. They're data. Insight requires interpretation, and interpretation requires judgement. The ability to distinguish between what's interesting and what's important. To understand context. To spot patterns. To reconcile contradictions. To know which customer truths should influence decisions and which should simply inform them.

AI can undoubtedly help with parts of that process, but perhaps the bigger question isn't whether AI should be used. It's whether we've spent so long talking about hearing customers that we've forgotten to explain why expert interpretation matters.

Maybe the biggest threat facing the insight industry isn't AI. Maybe it's that we've spent years convincing clients that the value lies in hearing customers rather than interpreting them.

If that's true, we shouldn't be surprised when someone asks for the transcripts and skips the thinking. Which raises an interesting question:

If a client wants the research but not the interpretation because AI can do that part, do we simply provide what's been asked for? Or do we have a responsibility to challenge the assumption?