Background: Self-sufficiency when shopping is a known challenge for visually impaired people in an ocular-centric society. Smartphones with AI computer vision and NLP technology offer great potential and can be used to scan objects and provide their user with verbal information about them, thus promoting inclusion in an important aspect of everyday life without having the stigma of assistive technology. However, understanding the relation between the human being, the object and the environment in which it exists is complex when sight is impaired. Method: The paper is based on video ethnography (Heath et al., 2010) of visually impaired people’s daily lives and usage of mobile scannings of products from grocery stores in Denmark. The paper presents video clips that are analyzed using ethnomethodological multimodal conversation analysis (Streeck et al., 2011). Results: The identified challenges for visually impaired people when scanning objects are to a) hold the phone correctly, b) find the correct angle of the camera, c) find the correct distance to the object, d) hold the object in the correct angle and position and e) understand the intrinsic nature of the object. We show just how visually impaired people accomplish this in-action despite their impaired sight. Discussion: Although AI technologies holds promises, this research shows how the technology needs to be adjusted and social practices learned in order for visually impaired people to achieve social inclusion. Heath, C., Hindmarsh, J., & Luff, P. (2010). Video in Qualitative Research. SAGE Publications Ltd. Streeck, J., Goodwin, C., & LeBaron, C. (2011). Embodied Interaction: Language and Body in the Material World. Cambridge University Press.