Over 700 professionals detailed the specific failures and data hurdles slowing visual and physical AI production. The survey identifies data curation as the primary friction point for teams building embodied systems. These findings confirm that raw data volume matters less than quality. Practitioners must now prioritize precise data pipelines over larger datasets to improve model reliability.