What are the biggest challenges you face when sourcing high-quality, domain-specific datasets for training and evaluating AI models?

AI practitioners report that sourcing high-quality, domain-specific datasets remains a major hurdle, particularly for multimodal, multilingual, and human-annotated data, according to a query posed to industry experts. The primary challenges include ensuring reliability for production AI and establishing clear criteria for dataset quality.

I’d be particularly interested in experiences with multimodal data text, audio, image, video , multilingual datasets, and human-annotated data—and what criteria you use to determine whether a dataset is reliable enough for production AI.