John LaurensonBusiness Reporter, ParisGetty ImagesCollecting opinions is time consuming work"When you hear the word 'politician', what is the first image or emotion that comes to mind?"The voice is young, female, brisk and business-like and belongs to an AI agent. A computer programme in other words. A string of code.A man on the other end of the line replies.
While he's airing what is a pretty cynical opinion of politicians, three other AI agents process what he's saying.One checks he's answering the question, one analyses whether he's being too superficial and needs prompting to go deeper, while the third checks that the respondent is not a fraud… not a robot, for example.This poll is being conducted by a French AI opinion poll company called Naratis."The US has start-ups like Outset, Listen Labs and Hey Marvin that do AI polling like this in the commercial sphere. To my knowledge we're the first to do this for political opinion polling as well," says Pierre Fontaine, the 28-year-old engineer who founded the firm in 2025.What was once the most labour-intensive corner of opinion research is becoming one of its most automated.In France, as elsewhere, that shift is beginning to reshape how public opinion is measured, understood - and potentially influenced.Naratis aims to take qualitative research - the slowest, most expensive form of polling - and rebuild it around AI.Traditionally, qualitative studies involve small groups or one-on-one interviews with paid respondents recruited via panels. These interviews can take weeks to conduct and analyse.
Naratis replaces that process with conversational AI.It does not focus on quantitative polling, which is already largely automated through mass surveys. Instead, it emphasises depth. "We don't ask people to tick boxes - they have a conversation with an AI," Fontaine explains.
"That means we can explore not just what people think, but how they think - how they build their opinions, and even when those opinions change."The company claims its method is "10 times faster, 10 times cheaper and 90% as accurate as human polling".A study that once took weeks and tens of thousands of euros can now be completed in a day or two. Responses can often be gathered in under 24 hours, allowing clients to react to events almost in real time.This speed comes from what Fontaine calls "parallelisation": instead of human interviewers working one by one, AI agents can conduct many interviews simultaneously.PolynomStéphane Le Brun (right) notes responses to surveys have slumped since the 1990sThe rise of AI polling comes at a difficult moment for the industry. Response rates to surveys have fallen sharply, from over 30% in the 1990s to below 5% today, according to AI consultant Stéphane Le Brun.
As fewer people respond, polling becomes both more expensive and less representative, fuelling public distrust.So what about Naratis's claim of near-human accuracy?Critics might point to past polling failures, such as the inability to predict Brexit or Donald Trump's 2016 victory. Fontaine argues that such problems mainly affect quantitative polling.Qualitative research, he says, is less about predicting outcomes and more about understanding opinions - for example, testing reactions to a campaign slogan rather than forecasting a vote.Across the industry, established polling firms are also integrating AI. At Ipsos, it is used extensively in market research.
Instead of asking people to describe their habits, researchers may ask them to film themselves, with AI analysing the footage. This allows companies to observe behaviour directly, rather than relying solely on self-reported data.Getty ImagesPolling of US swing states in 2016 failed to forecast Donald Trump's victoryAI is also used to analyse social media and to experiment with "digital twins" and "synthetic people". A digital twin is a virtual model of a real individual, designed to respond in similar ways.
Extract — continue reading at the source.
.jpg)
