AI-powered search: Faster, more intuitive asset discovery

Users want to find assets by describing what they are looking for in natural language, so that relevant results appear even when the exact filename or keyword is not known. Problem / Pain: Finding the right asset often requires knowing the exact filename, tag, or keyword it was filed under. Users who are unfamiliar with the existing tagging structure, or who simply want to search more naturally, currently have limited options. Conventional keyword search only returns results that match the entered term precisely, which means relevant assets can easily be missed. Impact / Benefit: AI-powered search understands the meaning behind a search term rather than just matching it literally. This makes asset discovery faster and more intuitive, especially for new users, users unfamiliar with the tagging conventions, or anyone looking for assets based on content or context rather than exact metadata values. Example use case: A marketing user is looking for images showing a dog for a campaign. Instead of knowing which specific keywords or tags were used when the assets were uploaded, they simply type "dog" into the search and receive relevant results, including assets that match the concept even if the word "dog" does not appear explicitly in their metadata. Idea source: User Feedback Voting note: Vote for this idea if this need is relevant to you as well.