What I’ve Learned Co-Hosting the MRII Podcast: AI Presents A Unique Opportunity for Insights to Reinvent Itself

Over the past six months, I’ve had the privilege of co-hosting the MRII Insights & Innovators podcast, alongside industry stalwarts such as Niels Schillewaert, Jon Last, Stan Sthanunathan and Z Johnson.

It’s been an incredible opportunity to interview Insights leaders, CMOs, behavioral scientists, agency partners and technology founders – and hear their perspectives on where Insights is heading.

Inevitably, we’ve talked a lot about how AI is reshaping our industry: through automation, agents, AI-powered moderation, synthetic respondents and more. But across those conversations, one takeaway has stayed with me.

For all the talk about AI being an existential threat to Insights, I’ve come away believing the opposite: it represents an extraordinary opportunity to reinvent it.

Rather than resisting the automation of work that has consumed overloaded Insights teams for decades, we should embrace the capacity it creates to reimagine our role.

Across the episodes I’ve hosted so far, four themes have stood out.

1. We Need to Use AI to Reimagine Research, Not Just Make It More Efficient

Much of the conversation about AI still focuses on efficiency. But what if AI doesn’t simply make today’s research faster? What if it can make it better?

Alfred Wahlforss, CEO of Listen Labs, introduced me to the Jevons paradox: when something becomes dramatically more efficient, we often consume more of it, not less. He believes research could follow the same pattern. With AI increasingly able to write surveys, moderate research, analyze data and create reports, we could find ourselves doing more research, more frequently and iteratively than ever before.

Ricardo Dalmas of Kimberly-Clark described this as allowing us to “release our curiosity.” When every question doesn’t require a new project, budget and weeks of work, we can ask more questions and learn continuously.

Pankaj Chopra of Edgewell argued that rather than bolting AI tools onto existing processes, we should use them to rethink the broader research system and workflows.

And Stefano Puntoni of Wharton captured the opportunity perfectly: instead of using GenAI to “do things better,” focus on “doing better things” – from just-in-time insights and hard-to-reach audiences to entirely new forms of data and experimentation.

The opportunity isn’t simply to do today’s research faster. It’s to learn in ways that weren’t possible before.

2. As AI Increasingly Automates Research, We Need to Redefine Where Humans Add Value

If AI can automate much of the heavy lifting involved in running and analyzing research, where does that leave us?

Stacy Taffet, Chief Growth Officer at Hershey, gave perhaps the simplest answer: “The fact is… AI can’t feel.” Algorithms can identify patterns, but they can’t experience joy, nostalgia, humor or surprise. Making sense of those emotions requires a deep understanding of human motivations, culture and behavior.

Alfred highlighted another role. As AI generates vastly more information than any stakeholder can absorb, someone still has to frame the right question, understand the context and determine what actually matters.

Vineet Mehra, CMO of Chime, argued that while Insights professionals need to become genuinely AI-native, they need to use the capacity created to find the “golden nuggets” connecting consumer needs to product, brand and business strategy.

Ricardo also added a future-facing dimension: AI excels at finding patterns in the past, but human behavior isn’t always predictable. Understanding what people might do next requires empathy, imagination and foresight.

The goal shouldn’t be to keep humans involved in every part of today’s process. It should be to shift our time toward where we add greatest value: framing, empathy, context, judgment, imagination and foresight.

3. As AI Changes How We Conduct Research, We Need to Focus More on Outcomes, Not Outputs

If AI frees us to spend less time executing research and more time applying what we learn, our definition of success should change too: less “did we deliver great outputs?” and more “what outcomes did we drive?”

Elizabeth Oates of Molson Coors told a compelling story about presenting work, only to be told it was “really interesting.” Her reaction? “I’m not here to be interesting. I’m here to move the business forward.” That means starting with the business decision – not the research question.

Oksana Sobol of Clorox goes further: stop “shipping research decks” and start shipping decisions. She has redefined her team’s outputs as growth ideas and business decisions. An insight, in her words, is only a “half product” because its value comes from what happens next.

Ricardo makes that tangible: follow your work through the organization. What decision was made? Was the recommendation used? What happened next?

If AI gives us back capacity, let’s reinvest it in making sure our work actually changes something.

4. As AI Transforms Our Industry, We Need to Reimagine Ourselves as Organizational Leaders

If AI changes how we learn, where humans add value and how we measure success, then the role of Insights itself has to change.

Michelle Gansle gave me my favorite metaphor for that future role: the “orchestra conductor.” We don’t need to be experts at playing every instrument. Rather our value will increasingly lie in orchestrating AI, analytics, research, human expertise and business context around the problem.

Ricardo describes a similar future: Insights as a strategic copilot, working alongside decision-makers to frame problems, connect evidence, bring objectivity and drive better decisions.

Roger Jackson and Dr. Tim Holmes highlighted the critical importance of this role. Organizations are inherently susceptible to bias, conventional wisdom and groupthink, meaning Insights can provide the critical thinking and constructive challenge that helps leaders question assumptions.

Jing Mertoglu of Suntory Global Spirits added that, in order to become more effective leaders, we also need to think not only about our evidence, but how we engage the people making them… use our energy as multiplier effect,

Summing it up, Oksana argued that Insights professionals increasingly need to act as business leaders. Being right isn’t enough any more. We need to take a point of view, challenge assumptions, build conviction and help the organization act.

Influence isn’t a soft skill added on top of being a great researcher. Increasingly, it’s becoming a core part of the job.

An Opportunity to Reinvent Insights

I expected many of my podcast conversations to focus on what AI is taking away from our profession. But I’ve come away thinking much more about what it could give us.

AI gives us the opportunity to finally become the function many of us have always wanted Insights to be: to reimagine research, elevate the human contribution, focus on outcomes and ultimately drive better business decisions.

As we head into the next series of episodes, I’m looking forward to hearing from more of the people shaping our industry. If the conversations so far are any indication, the most exciting chapter for Insights may still be ahead of us.