For the complete argument, including all four insights and the Verso point of view, download the Women in Research POV report (PDF) here.

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The panel brought together Cyrielle Triolet, Director of Customer Knowledge at Orange; Marion Rossi, head of the qualitative practice at Institut CSA; Téja Falleh, Account Director at Dynata; and Lydia Bellahouel, co-founder and CEO of Verso. Emmanuel Huet, formerly of BCG's Center for Customer Insights, moderated.

Here is what they landed on.

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Why real-time insight is still a fantasy, and why that's good news

Real-time insight does not exist yet, and the panel was glad it doesn't. AI is not short on speed. It produces a great deal of material, fast. The work that remains is the work that always mattered: sorting that material, interpreting it, then deciding. A question asked without thought upstream returns a disappointing answer, quickly. "It does everything by itself" is the surest way to make a bad decision with confidence.

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"The fantasy is real time. We're not there. And that's a good thing." — Marion Rossi, Institut CSA

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What this means for consumer teams: speed is now a given, judgment is not. A large share of your value sits in the quality of the question you ask and the decision that follows the answer.

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Does running more interviews turn qualitative into quantitative?

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No. Platforms now let you run hundreds of open-ended interviews, which tempts people to think the line between qualitative and quantitative has dissolved. The panel drew it differently. Quant measures, reassures, sets a price. Qual explores, decodes, catches what goes unsaid. Multiplying interviews does not mechanically convert one into the other. Even at 250 respondents, the insight comes from the quality of the analysis, not the headcount.

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"There are subjects I refuse to handle quantitatively." — Cyrielle Triolet, Orange

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What this means for consumer teams: pick the method from the need, not the trend. Scale is a strength when it serves depth, not when it dilutes it.

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Why method matters more as insight becomes everyone's job

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The more accessible insight becomes, the more the methodological frame decides its worth. When anyone can query an AI and get an insight in seconds, the risk is no longer a shortage of answers. It is a flood of unframed ones. Methodological rigor and the governance of these tools stop being technical footnotes and become the core of the job. The insight function does not vanish behind the tools. It takes on a second role alongside production: guardian of the frame. Which method for which need, which limits for which AI, what quality of input goes in.

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"The more insight becomes accessible to everyone, the more central the role of method guardian becomes." — Lydia Bellahouel, Verso

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What this means for consumer teams: your legitimacy rests as much on the rigor of the frame you set as on the data you produce. Set the frame before you open the tools, not after.

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How speed brings qualitative research into decisions it never reached

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The real gain is not running the same study faster. It is running a qualitative study where, until now, there was none, because there was no time for one. A strategic plan written at year-end, a decision window of a few days: teams used to settle these on conviction, with no consumer voice in the room. Now they can interview real respondents and bring back a solid qualitative signal in about ten days. Qual stops being reserved for large, planned setups. It becomes something you can reach for in moments where it was structurally absent.

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"In ten days we can now say something we'd never have known how to produce before." — Cyrielle Triolet, Orange

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What this means for consumer teams: speed is not just comfort, it is reach. The faster qual is to mobilize, the more decisions it can inform that used to be made without it.

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What this changes for consumer teams in 2026

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Understanding a need before answering it, framing the right method, reading emotion and the unsaid, turning data into a decision. That craft does not delegate to a tool. At the center of all of it sits a human: the consumer you interview, whose words stay the raw material of every insight. AI replaces neither the researcher nor the person across from her.

What changes is access to that voice. Collecting what a real consumer thinks used to take time, fieldwork, and a cost that capped how many people you could listen to. That voice is now simpler to reach, faster, and at greater scale. The same depth, available when you need it and as often as you need it.

This is where the field opens up. When listening to real people becomes quick and affordable, new uses of qualitative appear. Test an idea between two meetings. Feed a strategic plan while it is being written. Probe a segment you'd never have had the budget to explore. These uses do not replace the large planned setups, the face-to-face sessions, the brand-equity deep dives. They add to them. Qual does not shrink. It gains ground.

The evening was a first edition, not a conclusion. The conversation continues, and we intend to carry it on with the people who do this work.

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Watch and read more

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The full panel replay is available.

For the complete argument, including all four insights and the Verso point of view, download the Women in Research POV report (PDF) here.

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FAQ

What was Verso's Women in Research evening?‍

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A panel held on 14 June 2026, bringing together four senior women in consumer research from Orange, Institut CSA, Dynata and Verso to discuss what AI has actually changed in the discipline.
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It was the first edition of the series.
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Can AI deliver consumer insights in real time?Not in any way worth trusting. AI generates material quickly, but the work of framing the question, interpreting the output, and deciding what to do still takes human judgment. A poorly framed question returns a poor answer, just faster.

Does running hundreds of AI interviews turn qualitative research into quantitative?No. Even at 250 respondents, the insight comes from the quality of the analysis, not the sample size. Quant measures and sizes; qual explores and decodes what consumers don't say outright. Volume alone doesn't bridge them.

Does AI replace consumer researchers?No. AI changes access to the consumer's voice, not the craft of interpreting it. Understanding a need, reading emotion and the unsaid, and turning data into a decision still rest with the researcher.

How fast can AI-powered qualitative research deliver results?Verso runs adaptive AI interviews and returns a solid qualitative signal in around ten days end to end, fast enough to inform decisions that used to be made with no consumer input at all.

What does AI change for consumer insights teams in 2026?It makes the consumer's voice faster and cheaper to reach, which expands where qualitative can be used. It also raises the premium on method: framing the right approach and governing the tools becomes central to the role.

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