4 AI Applications Powering Digital Asset Management

Amidst the growing complexity of managing digital content, media firms can immensely benefit from the incorporation of AI.

FREMONT, CA: The exponential rise of digital content across the industries has made the task of asset management difficult for the organizations. It is a tedious task to categorize massive numbers of digital content for future reference manually. Digital asset management is assisting the firms by enabling a smooth creation, design, and distribution of the content. Meta-data forms an integral part of asset management, which contains various information about the digital file such as the date, author, and size of the file. Such kind of data allows the categorization of the files based on desired specifications. Artificial intelligence (AI) is the key technology that can help with the tedious task of metadata or asset tagging. 

The shift from local network storage to cloud-based storage is one of the prime factors which is leading to the rise of AI in digital asset management solutions. AI can assist the cloud-based asset management solutions by refining the metadata related to the vast array of digital files. Using AI, thousands of new as well as existing assets can be effectively categorized in a short period of time. Here are the features through which AI can aid digital asset management efforts.

 AI-Generated Metadata

Based on the vast array of data over digital files, AI can filter the relevant metadata and categorize digital assets. AI offers an opportunity for organizations to toggle between human AI-generated metadata. Further, the self-learning capability of AI algorithms will significantly improve the relevance of the AI-generated metadata. Thus, AI can unlock the potential of all the existing content and make them traceable, reusable, and monetizable.

 Natural Language Processing

AI incorporation can significantly enhance digital asset management capabilities with the help of powerful tools such as automatic language and speech-to-text translation. With the help of such tools, AI allows the firms to tag assets automatically based on factors such as location, people, and even sentiment. With the growing sophistication of AI tools, image and video processing capabilities of the digital asset management solution will significantly increase.

 Facial and Speech Recognition

A robust AI-driven facial recognition technology distinguishes an average digital asset management solution from an exceptional one. Facial recognition capability in asset management allows searching images and videos and categorizing them based on age, gender, and location of the subjects. Such systems can also identify speakers by searching throughout the web-based databases containing millions of speech records. 

Apart from recognizing humans, such systems can recognize objects too. The above tools also offer optical character recognition (OCR) along with full speech detection enabling both on-screen text and speech fully searchable.

 AI-Guided Delivery

AI enables digital asset management systems to offer enhanced efficiency. Enterprise asset management also becomes more scalable with the incorporation of AI. An effective asset management solution assists the firms in addressing omnichannel content delivery to the customers. Moreover, a robust digital asset management solution allows the media firms to route content based on tagging, thereby offering a level of automation to the existing asset management solution. The automation features may include the ability to perform management of scheduled publishing using a content management system. Such automated delivery features assist in targeted syndication, enabling automated media delivery to micro-sites and syndication partners.

 AI's contribution to digital asset management solutions will pave the way for efficient storage and reusability of the existing as well as emerging content. Media firms are realizing the aforementioned potentials of AI and are incorporating the technology to stay ahead competitive.

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