My Reflections on Insight Out

At last week’s Insight Out conference in San Francisco, I shared an idea that, at first, felt a bit unintuitive: AI isn’t making research less human—it’s actually making it more human. To my surprise, that message really resonated. The tools we’re building today aren’t about replacing people. They’re helping us understand them faster, deeper, and at a scale that just wasn’t possible before. In this post, I want to unpack that idea—drawing some inspiration from the rise of computing, exploring how research workflows are evolving, and sharing what teams like Nestlé are doing to bring more human insight into every decision.

Back in the early days of computing, mainframes were powerful—but incredibly expensive. Because computing was costly, we used it sparingly, for only the most critical tasks. But as the cost dropped, everything changed. We didn’t just compute more—we reimagined what computing could be. Entire categories of products and experiences became possible.

That same shift is happening in research. When interviews are expensive and time-intensive, we’re forced to be selective: one study, one market, one hypothesis at a time. But when AI lowers the cost per insight, we’re not just doing more of the same research. We’re unlocking an entirely new layer of possibility: faster iteration, broader reach, deeper exploration. Research becomes something teams can embed directly into the creative process, not just validate outcomes after the fact.

AI isn’t just speeding things up—it’s changing what’s possible. With AI-moderated interviews, teams can now run hundreds of conversations at once, across time zones and languages. And it’s not just a transcript generator. Today’s tools can pick up on tone, emotional cues, and ask smart follow-up questions, just like a skilled moderator would. Then, instead of weeks of analysis, we get synthesized insights in hours. That means teams can move faster, with richer inputs and more human-centered outputs.

Take Nestlé. They’ve got over 2,000 brands and a constant stream of product ideas. Traditional research methods just can’t keep up. So they partnered with Outset to help test over 100 concepts across markets without slowing down. What’s exciting is that they didn’t have to trade depth for speed. AI helped them gather qrualitative insights at scale, faster and more affordably, while including voices that might otherwise get missed. That speed and inclusivity helped Nestlé move quickly from concept to market, without cutting corners on understanding.

But what’s maybe most exciting to me is how AI is helping us listen—not just more broadly, but more deeply. It removes the friction that keeps so many people from being heard: time zones, scheduling conflicts, accessibility barriers, even social anxiety. Whether it’s a rural shopper or a busy parent, more people now have a voice in shaping the products and services they use. That’s the real shift. Research has always been about understanding people, and AI is giving us a chance to do that better than ever before.

As this technology becomes part of the day-to-day, the role of the researcher is changing too. We’re moving from being moderators and scribes to being sense-makers—zooming out, spotting patterns, and helping teams move with confidence. Of course, it comes with new responsibilities. We have to use these tools thoughtfully: be transparent with participants, protect their data, and stay alert to bias. This isn’t just a new toolset—it’s a mindset shift. One that blends speed with care, and scale with empathy.

So, no—AI isn’t here to replace human understanding. It’s here to amplify it. To knock down walls that made deep research hard to scale. To make space for more people to be heard, and more teams to move forward with clarity. That’s what I left the conference feeling most hopeful about. We’re not becoming less human—we’re building a future where understanding people is central, and more possible than ever.