TY  - JOUR
TI  - Generative AI adoption in 3D animation production: a pipeline-wide empirical benchmark of early-career practitioner perceptions and the HGAI hybrid pipeline framework
AU  - Sandeep Maithani
PY  - 2026
DA  - 2026/07/24/
JO  - Multimedia Tools and Applications
AB  - Sandeep Maithani (School of Multimedia, Lovely Professional University, Punjab) surveyed 126 students, educators and early-career practitioners about generative AI use across every stage of the 3D animation pipeline. Adoption is heavily front-loaded: storyboarding (45.6 percent) and concept art (41.6 percent) lead, while rigging assistance (16.0 percent) and denoising (10.4 percent) trail. Respondents rated current tools' reliability at a mean of 2.95 out of 5, with output inconsistency the most cited barrier (46.4 percent). Professionals used the tools more intensively than students but rated reliability no higher. From the stage-by-stage split the author derives a human-guided AI (HGAI) pipeline model with three phases: AI-led stages where adoption is 40 percent or more, hybrid stages between 20 and 39 percent, and human-led technical stages below 20 percent adoption and below 3.0 out of 5 on reliability. The sample is small and India-weighted, the reliability measure is a single item, the design is cross-sectional and the article is paywalled; the survey data is published openly on Zenodo.
KW  - generative-ai
KW  - production-pipelines
KW  - 3d-generation
KW  - studio-pedagogy
KW  - labour-and-workforce
KW  - survey
UR  - https://link.springer.com/article/10.1007/s11042-026-21795-5
LA  - en
ER  -