This work presents one of the earliest documented cases of a fully AI-driven audiovisual production pipeline applied to institutional promotion in Spanish higher education. Unlike conventional workflows, where artificial intelligence is used as an auxiliary tool for editing or enhancement, this study places generative models at the core of the entire production pipeline, including motion synthesis, visual composition, and editorial assembly.The paper introduces a formalized generative production framework and evaluates it against traditional capture-based audiovisual workflows in terms of cost structure, scalability, iteration flexibility, and environmental impact. The analysis is grounded in a real institutional case study: a university promotional video created by Javier Ortiz Zamora using a fully generative pipeline.The results show that generative audiovisual production can significantly reduce reliance on physical filming, logistics, and reshooting, while enabling new forms of creative control and sustainable media production.This work contributes to the emerging field of AI-driven media production by providing both a conceptual framework and a real-world validated case in the context of higher education.
ZAMORA et al. (Tue,) studied this question.