Olivier Touba: What would your digital twin say?

Mar 23, 2026

Olivier Toubia, a Columbia Business School professor who studies AI, marketing and digital twins. He explores how LLMs pull toward the average, why synthetic consumers struggle in politics, and how digital twins show pro-tech and privacy-light biases. He also discusses monetisation paths for generative AI, uneven business adoption, and where AI can and cannot mimic human creativity.

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ANECDOTE

People Form Emotional Bonds With Chatbots

Users form emotional attachments to chatbots; some reported feeling 'they lost a friend' after a model change.
Toubia cites reports of people, particularly young people, having romantic relationships with AI agents.

ADVICE

Validate GenAI Pilots Before Scaling

Test GenAI pilots rigorously and temper executive optimism with realistic ROI expectations.
Toubia cites reports that 90–95% of corporate pilots fail and says 2025 is the year leaders demand measurable results.

INSIGHT

Top-Down Push Meets Bottom-Up Resistance

Adoption is uneven: senior leaders push GenAI while middle managers and employees resist due to job-threat fears.
Toubia notes resistance is rational because automation can meaningfully reduce headcount and even threaten managers.

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Olivier Toubia is a Columbia Business School professor working at the frontier of AI, marketing, consumer behaviour, and digital twins. This was recorded late last year but his arguments are relevant and clear: LLMs drive towards the average which means its hard to mimic the diversity of human existence.

Digital twins are promising — but not ready. Synthetic consumers for research purposes (e.g. virtual focus groups) are fast and cheap, but Toubia’s research suggests they are still too biased and inconsistent to trust too far. Learn what happened when they compared digital and human twins' responses to the same questions.
Politics is the worst domain to deploy synthetic focus groups: The base model exerts a powerful pull. Twins often reflect the worldview of the model as much as the individual they are meant to represent, especially in politics, where performance is weakest. AI is too sensible - compared to humans it tends to be more moderate: in one study 45% of humans wanted to deport illegal immigrants and only 5% of digital twins agreed.
Synthetic personalities reflect a clear pro-tech bias. Twins tend to be more comfortable with algorithms, less concerned about privacy, and more trusting of technology than humans actually are. AI twins thinks AI is smarter than humans....
Generative AI has entered its monetisation phase with advertising as the likely endgame Subscriptions and enterprise sales matter, but the bigger prize is becoming the interface for search, discovery, decision-making, and purchase.
Business adoption remains uneven but labour anxiety is rational Many pilots are failing to deliver meaningful returns; senior leaders are often enthusiastic, while middle managers and employees are more sceptical.
AI can be creative, but not at the edges. AI tools can recombine ideas - "its a fallacy to think that AI will never be able create new things". However, it still misses the diversity of lived experience that gives humans their edge. The push is towards the average.

We usually worry about AI driving polarisation - Olivier's work shows that current LLM tools trend towards the opposite. Humans can provide the spikiness and AI the padding.

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