Artificial Intelligence (AI) Tagging refers to the use of AI technologies to automatically generate metadata tags for digital assets.
What is AI tagging in DAM?
In the context of Digital Asset Management (DAM) systems like ResourceSpace, AI tagging can significantly streamline the process of organising and retrieving digital files. By leveraging machine learning algorithms and computer vision, AI can analyse the content of images, videos and other media to identify objects, scenes and even emotions, subsequently assigning relevant tags without human intervention.
Benefits of AI tagging for large image collections
The primary advantage of AI tagging is its ability to handle large volumes of digital assets quickly and accurately. Traditional manual tagging is not only time-consuming but also prone to human error and inconsistency. AI tagging mitigates these issues by providing a consistent and scalable solution. For instance, in a DAM system, AI can automatically tag thousands of images with descriptors such as "beach", "sunset" or "conference," making it easier for users to search and locate specific assets based on these tags.
What’s more, AI tagging can enhance the discoverability and usability of digital assets. By generating detailed and contextually relevant tags, AI helps ensure that assets are more easily found through search queries. This is particularly beneficial for organisations with extensive media libraries, such as marketing agencies, media companies and educational institutions. Enhanced searchability not only improves workflow efficiency but also maximises the value derived from digital assets by making them more accessible to users.
AI tagging in ResourceSpace
Our AI tagging functionality offers ResourceSpace users numerous ways for improving and automating metadata processing tasks, including:
- Automated image tagging and description: automatically tag and describe images based on their content, improving searchability and categorisation.
- Facilitation of rights management: recognise objects, scenes or even text within images which can assist in rights management by identifying copyrighted material or trademarks.
- Automated title/summary generation: generate concise and descriptive titles and summaries from large blocks of text, like a PDF file, subtitles from a video file, or pulled in from a Collection Management System or Product Information Management system.
- Keyword extraction: automatically extract meaningful keywords from a block of text, providing a list of relevant keywords for searching, categorisation and more.
- Automatic categorisation: AI tagging can be used to automatically categorise digital assets based on their content, saving time and ensuring consistent and accurate categorisation.