Innovative Air Mobility (IAM) is expected to enhance regional connectivity. However, its successful deployment depends on understanding who is willing to adopt IAM, how much demand it can realistically capture, and the extent to which it can generate new trips. To address this, this paper develops a hybrid behavioural–big data framework to model IAM demand. A stated preference survey is used to estimate a multinomial logit model. The behavioural model is then transferred to large-scale origin–destination flows derived from mobile network data. The methodology is applied to different OD pairs in the Catalonia region, Spain. Results show that IAM uptake varies significantly across corridors, reaching up to 22.6% in intra-regional trips but remaining below 7% in longer corridors, with demand primarily substituting car travel. Induced demand emerges only under low pricing scenarios and is concentrated among high-income, time-sensitive users, highlighting IAM’s role as a premium, niche mobility service rather than a mass transport solution.