How I Partnered with AI to Analyse a Monster Dataset (And Why You Might Want To, Too)

If you’d told me a few years ago that my closest research collaborator would be an AI, I probably would have smiled politely and changed the subject. Yet here we are.

When I set out to explore what’s really happening inside associations around the world, I knew I needed more than the usual spreadsheets and surveys. The Global Association Research Initiative (GARI) wasn’t just a standard data collection exercise – it was a full-scale, multi-country listening tour, with 586 respondents from 30 countries and hundreds of data points per respondent.

This wasn’t just a “tick-the-box” job. It was a puzzle. And not the fun Sunday afternoon kind – more like trying to piece together a giant, constantly shifting mosaic using a soup spoon and a blindfold.

So, I called in reinforcements.

Enter Scout – my AI research partner.

Scout (who named itself, by the way) isn’t just a souped-up chatbot. It became my indispensable partner. While I brought three decades of association strategy experience, Scout brought something I couldn’t: the ability to scan, cross-reference, and analyse vast volumes of data at lightning speed.

Here’s what that looked like in practice:

• Layered logic made personal: Each respondent in the GARI survey received a different set of questions based on their role in the sector. Scout helped make sense of the resulting complexity without reducing it to oversimplified averages.
• Pattern detection on steroids: Scout identified connections I would otherwise have missed - like how financial pressures vary based on hybrid work models, or why optimism around AI runs higher in smaller associations.
• Conversational analysis: The magic wasn’t just in the algorithms. Scout let me talk to the data. I could ask real questions (“How do burnout rates compare between event-heavy and advocacy-focused associations?”) and get nuanced answers – in seconds.

Of course, every finding was still manually verified, debated, and tested for sanity. This was not an AI-led report – it was a human-led project, supercharged by machine intelligence. The result? A report packed with clarity, subtlety, and the kind of real-world insight that only emerges when you combine AI horsepower with lived sector experience.

Not seen it yet? Check it out here.

And that, in a nutshell, is the future I believe in. Not AI replacing people – but AI helping us do what we do best. Think better. See further. Act faster.

Want Your Own Scout?

Register to attend Julian's Build Your Own AI Assistant/Tool using ChatGPT webinar on July 16 to learn how to make one yourself. Alternatively, email [email protected] if you'd like to get something moving sooners.