AI for Insights: Lessons from The Insights Association’s 4-Part Series

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For Market Research and Insights professionals trying to keep up with AI trends, it’s no easy task. We’re constantly bombarded with new tools (and the sales pitches to match). And for the thoughtful researcher aiming to deploy AI for real ROI, it gets even more complex—because both general-purpose LLMs (ChatGPT, Gemini, Mistral, etc.) and research-specific tools (like those from Dovetail, Dscout, PlaybookUX, Recollective, and many others) may be relevant.

 

With both types of tools in the mix, the landscape can feel like a sprawling music festival: lots of acts, lots of hype, and limited time to figure out which ones are worth your attention. That’s why choosing tools isn’t the first move. The real starting point is identifying your most relevant use cases.

 

That theme came through loud and clear during the Insights Association’s recent four-part webinar series, AI for Insights: How & When to Work with the Leading Platforms. While the focus was on LLMs, each one was demonstrated in the context of real, practical use cases.

 

I had the pleasure of co-moderating this webinar series with Jeff McKenna, data scientist at Leger and one of my long-time favorite quant researchers.

 

The series focused specifically on LLMs and featured real-time demonstrations by:

  • Scott Swigart, demoing Gemini and Claude in side-by-side action
  • Joe Galarneau, evaluating Llama, DeepSeek, and Mistral (scorecard included!)
  • Ray Poynter, showing how ChatGPT supports real analysis work
  • Romani Patel, demonstrating Copilot for real-world research tasks

Each speaker shared real use cases—no AI hype, just practical applications we can learn from.

 

AI Use Cases for Market Research & Insights

The expert speakers shared examples tied to various AI use cases, including research planning, text analysis, data summarization, and more. Of course, with the time limitations of a webinar series, they couldn’t cover every use case—but they did a great job highlighting a wide variety.

 

And if you’re still mapping out your team’s AI roadmap, there are plenty of use cases to consider—whether for near-term wins or longer-term piloting and adoption. In fact, I’ve been keeping a running list of AI use cases for research and insights (26 and counting!), including:

  • Meeting notes & action plans
  • Questionnaire, screener, or discussion guide design
  • Automated survey translation and localization
  • Anomaly detection and outlier identification
  • Data visualization
  • Qual & quant research report generation

 

Whether your team is starting its AI journey with personal productivity, improving data collection, enhancing analysis, or accelerating deliverables, there’s likely an AI-powered option worth exploring.

 

The AI Learning Journey

I’m having a blast building my own AI knowledge—just like many of you. For more details, I invite you to read my full recap article for the Insights Association: