In some ways, the ingredients to conference success are similar to that for focus groups. Creature comforts are key. In this regard the 2023 Future of Insights Summit by CRIC / ESOMAR / CAIP delivered: I found the food was tasty, particularly the mushroom-stuffed tortellini.

The atmosphere at a conference can be many things, bustling, exciting, edgy, relaxed, calm, boring. While most people are probably there to make connections, I find it a bit embarrassing to witness attempts at buttering up potential clients and outshining other vendors at the table. Fortunately, there wasn’t too much of that and I felt the overall atmosphere was friendly and relaxed.

In terms of topics, I believe most people came to the conference to learn about AI. I heard several echo my own sentiment when the topic at last took centre stage, in the afternoon of day two: “finally”!

And what did we learn about AI? Steve Mossop played a scary “view into the future” reel suggesting that in a short amount of time we could all become slaves (or pets?) to “the machine”. He also mentioned that Leger is testing it, for all insights-related things – proposal writing and questionnaire design, coding, open-ended probing, analysis, charting – so far with limited impact on the business.

Frank Graves of EKOS presented data suggesting that a large proportion of Canadians are familiar with AI, with sharply increasing tendency. I wasn’t sure what to make of these data points. I think in this context the word “familiar” can mean many things. I doubt that it means actually understanding how AI works, and how machine learning is different from simply applying algorithms.

In terms of the actual, current uses of AI in the insights industry, two use cases were demonstrated on stage. One is the coding of open-ends. Using GPT4, Brenden Sommerhalder from MQO Research showed how AI comes up with a code list, and how you can improve upon the code list by running the AI over it multiple times. At the end, the result is pretty good, according to Brenden. Since code lists are a complex thing, we could not verify this on the spot. But MQO Research gave an access code for their GPT4 tool to all conference participants to try it out for free for the next few weeks. Pretty cool!

The other use case is having AI ask follow-up questions after an open-ended survey response. This is called “adaptive prompts” and is something that Kathy Cheng at Nexxt Intelligence offers to her clients. It is clear that by adding another prompt after an open-end, and one that is specifically tailored to your response, open-ended answers become much richer and survey engagement goes up.

This is certainly something to consider, since respondent engagement is one of the big issues in survey research – along with fraud, which was also discussed. Apparently, panel companies like Dynata and Sago are looking into using AI for improved fraud detection – ironically, while fraudsters may also be using AI to better disguise themselves.

So, I came away with the impression that many companies are looking into and experimenting with AI. There is a widespread expectation that it will transform our industry yet again. But it didn’t feel like the competitive struggle over who has the best AI application has yet erupted. AI is perhaps still too new, and too complex, and everyone is just feeling their way into it. There is palpable unease about its unknowability, and the new buzzword in our industry appears to be “guardrails”.  “Guardrails” means: We need to put something, anything, in place to make sure this fast-moving technology bus isn’t going to drive off the side of the cliff.