Demand for Conversational AI
Elliott Ash,
Francesco Capozza and
Sergio Galletta
No 12673, CESifo Working Paper Series from CESifo
Abstract:
Relational uses of conversational AI register as barely demanded in stated-preference data, even as the market for AI companions grows quickly. We estimate demand across five purposes (administrative assistance, studying, wellness, friendship, and romance) in a preregistered within-respondent conjoint experiment (N= 1,989) that independently randomizes price, privacy, personalization, modality, and safety policy. Purpose dominates every design attribute: respondents require $7.80 per month to accept a romantic companion in place of an administrative assistant, six to seven times the largest non-price feature effect. Making the product free does not close this gap: the zero-price premium is roughly halved for a romantic companion. Second-order beliefs are compressed across purposes relative to own interest, and the ratio of the belief–interest gap to the purpose penalty is statistically indistinguishable across the two relational purposes, as a single social-image cost parameter implies. That ratio doubles as the welfare statistic and does not depend on the price slope: if the entire gap is suppression, social image accounts for 39.5% of the romantic penalty and 46.6% of the friendship penalty. A hierarchical Bayes demand model recovers the taste distribution and shows that social-image sensitivity shifts relational tastes more than instrumental ones while leaving price and attribute sensitivities unchanged; belief shrinkage cannot account for the pattern, but the structural estimates imply that only 10–15% of the belief–interest gap is suppression, so most of the measured relational penalty is intrinsic taste.
Keywords: conversational AI; conjoint analysis; willingness to pay; social image; second-order beliefs; hierarchical Bayes (search for similar items in EconPapers)
JEL-codes: C81 C93 D82 M31 (search for similar items in EconPapers)
Date: 2026
New Economics Papers: this item is included in nep-ain and nep-exp
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