They say that content is king. However, it’s the kind of king you want to control and use as an asset in your digital campaigns. To ensure your reign over content, you need to be able to organize it properly, so you know where it is and what it does at any given moment. AI-powered Digital Asset Management (DAM) systems can do that, and much much more.
What Is Digital Asset Management (DAM)?
Digital Asset Management (DAM) is composed of a set of technological tools and business practices used for the collection, organization, enrichment, and distribution of digital assets.
Legacy DAM—Metadata for Rich Media
In the past, the term digital asset referred mainly to rich media content, such as text, images, and videos used for creating interactive ads. Legacy DAM tools operated mainly on basic metadata. You could add a few pieces of information such as file name, date, and file type, but not much beyond that. This is all you had to go on when you organized your rich media into collections and all you had to go on when you searched for files.
Marketing Technology (MarTech) DAM—Catalogues for Marketing Content
Today, the term digital asset includes a wide array of content types, such as vectors, animations, GIFs, PDFs, PowerPoint presentations, PSD files, and more.
DAM is no longer a basic tool. Rather, it’s a content hub that supports the marketing, promotion, and sales efforts of the organization. You can upload any media file, create catalogs and collections, organize, edit, and distribute the content.
What Is AI-Powered Digital Asset Management (DAM)?
In today’s content-led digital landscape, a DAM solution should operate as a centralized media management hub that supports the organization’s efforts. That means going beyond basic metadata, beyond catalogs, and beyond support for various content files. It means providing smart features that turn a digital asset management solution into a dynamic and agile platform. This is where Artificial Intelligence (AI) comes in.
AI enhances DAM solutions, enabling the speed and automation required to maintain visibility in a content-heavy digital sphere. Thus, an AI-powered DAM should always be:
- Fast—one of the main benefits of AI is the speed in which it can work. AI-powered DAMs can process information, in real-time, enabling dynamic media management capabilities. This feature is especially good for eCommerce websites that want to deliver personalized content to enhance customer experience and drive more sales.
- Automated—AI is the force behind many automation processes, taking over repetitive and manual labor. A great example is auto-tagging and automatic optimization. Enabling auto-tagging means the AI will tag images for you, and if you enable automatic optimization, the AI will analyze your content and either offer insights or act on them.
- Smart—this is perhaps one of the best capabilities AI adds to DAM solutions—the power to sort, filter, search easily, and organize. Many systems, like WordPress and other Content Management Systems (CMSs), simply don’t have the ability to organize huge loads of content. AI enables smart search, which ensures you can always find what you’re looking for.
How an AI Powered-DAM Works
Artificial Intelligence (AI) technology is used to enhance systems with speed, automation, and intelligence. The goal of AI systems is to take over tasks that require human intelligence, with as little human assistance as possible.
Ideally, an AI should be able to perform tasks that involve reasoning and learning, through the use of information, including perception and motion. It should then analyze the information, sometimes with the use of social intelligence and creativity, and create knowledge representations and manipulations.
Different AI systems will have a unique level of capabilities and autonomy, but every AI system should be able to collect and analyze information at the very least. AI systems use Machine Learning (ML) processes to learn, evolve, and assimilate human intelligence patterns. AI systems require huge amounts of data and, consequently, they also require time to learn.
Key AI Technologies That Power the Dynamic DAM Systems of Today
Applications of AI in DAM systems have proven widely successful in helping DAM users regain control over huge amounts of content. Below, you’ll find a review of the main AI technologies that power the dynamic DAM systems of today.
Auto-tagging
A tag is a keyword that adds a classification to digital assets. In most DAM systems, you can set up as many tags as you want, and use them as added metadata that refines your search, filters, and file sorting. Usually, DAM users need to apply the keywords manually, one by one, to each digital asset uploaded to the platform. That can take a long time.
Auto-tagging is a feature that delegates tagging tasks to the DAM solution. That means the AI system will scan the images, identify the objects in the image, and then use the appropriate keyword to tag the image. The AI can also use tags to distribute batches of content across multiple and integrated distribution channels.
Computer vision
When scanning images, AI systems use image recognition, object recognition, and facial recognition. The AI analyzes the image or video, looks for a reference that will help it identify the images, objects, and human features in the image. Together, these three recognition abilities provide the computer vision requires for classifying the image appropriately.
Computer linguistics
When scanning audio, AI systems use speech recognition and optical character recognition (OCR). The AI listens to an audio feed and uses Natural Language Processing (NLP) and deep learning neural networks to break speech into words and sounds. It looks for speech patterns, deciphers them, and offers a text representation of what was said. This can be useful when analyzing video and audio files.
Conclusion
AI-powered DAM systems provide control and visibility into digital asset repositories. A DAM with AI eliminates hours of manual work spent on tagging, organizing, distributing, and sometimes editing media content. Advancements in computer vision and NLP are making AI systems more powerful and reliable than ever, enabling the automation of more and more digital asset management tasks.
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