This thesis examines and defines the development conditions for ALFRESCO, an artificial intelligence framework designed for the cultural and semiotic interpretation of images. The goal is to identify technological opportunities, innovation spaces, and design trajectories that support the system’s realization. The research maps the technological landscape through a systematic patent and competitor analysis in the domains of computer vision, semantic representation, and computational semiotics, identifying gaps and evolutionary directions related to symbolic modeling, interpretable multimodal integration, and culturally adaptive systems. In parallel, a focus group with experts and potential stakeholders explores usage expectations, value drivers, and perceived risks, informing the system’s functional positioning and usage identity.