How Your DAM Needs to be in The Era of Generative AI

Generative AI uses AI algorithms to produce outputs in the form of images, codes, videos, data, and 3D representations based on the data on which they are trained. Content creation in various forms is at the heart of Generative AI; it is different from other forms or uses of AI, such as self-driving cars or data analysis. Generative AI has taken content creation to the next level, as performing a range of activities that needed human intervention to generate content, such as writing emails, social media posts, images, poems, formulas, etc., can now be carried out using trained data.

As almost all digital assets today are born digital, Generative AI will create assets in the digital world but at far greater speed and scale. The real impact will be customizing an infinite number of visuals, repurposing assets, rebranding, reaching new markets, conducting A/B testing, and making data-driven decisions. In fact, many variations can be created instantly, and many more options than before will be available for A/B tests. Rich media including videos, can be created at the click of a button. Generative AI has the ability to create images from scratch and those that don’t yet exist; hence has the potential to create intellectual property.

DAM vendors will need to integrate with Generative AI not only to get an edge over their competitors but also if they are to match customers’ expectations. It will increase the scope of their solution. From being a master repository of digital assets, it would add another dynamic capability and may also find itself in competition with creative tools and technologies, as it will expand DAMs ability to modify assets to several notches. The current capability of DAM is limited; for instance, in the case of images, only basic alterations such as flipping, re-sizing, cropping, and a few other things are possible.

However, Gen-AI textual interface can be used to instruct DAM about how users would want to alter an image kept in the archives. Changes that need a lot of expertise by a professional can be carried out through Gen-AI, such as altering expressions or ethnicity of humans. The process would be straightforward, and the manifested image would not even be needed to be stored but will be dynamically rendered. It will bring significant changes to the DAM market, something that did not exist before, and DAM providers must be prepared to face and embrace them.

While some of the benefits for DAM with respect to Generative AI are clear and visible, such as operational efficiency, workflow improvements, enhanced user experience, and better ROI, certain benefits are still new (and evolving). And the DAM industry is still coming to grips with them, as that’s the nature of AI. However, among the most prominent benefits are:

• Automation in Tagging and Categorizing: The process of categorizing and tagging enterprise assets with metadata can be automated through Gen-AI. Algorithms can be trained to conduct an analysis of the assets to auto-assign appropriate categories and tags. It can speed up the process, eliminate errors, and increase efficiency.
• Creating and Augmenting Assets: New asset generation is a critical efficiency that will lead enterprises (especially smaller enterprises by saving their money and resources) to boost productivity, be less dependent on resource expertise, and be self-sufficient to a great extent. 
• Searching and Retrieving: With advanced tagging and categorization, enterprises can fast-track searches and find similar assets, as Gen-AI can understand the “search context.” Moreover, Gen-AI content can be tagged as non-human generated content, and identification can be further streamlined.              
• Scaling: Whether it’s searching, uploading, or editing assets, manual processing may not be adequate due to the sheer volume of assets. Gen-AI will be able to speed-up processes, improve scalability through eliminating any congestions in uploading, approvals and usage.  
• Ease of Use: Gen-AI imparts quickness and convenience to DAM in terms of workflow management, removing redundancies and repetition of assets, and speeding up new asset creation. From synchronizing DAM with PIM to improved metadata management, usability takes a leap with Gen-AI. 

As Generative AI continues to evolve, the future of DAM will continue to progress with it. The real-time asset creation will offer organizations an unprecedented edge, something they never had before. Industries such as digital commerce and retail are all set to see significant changes in the way they manage their digital assets. 

The powerful asset customization capability without an expert’s help will be a game-changer for DAM. Deployment of Gen-AI within content creation workflows has already begun and user prompts or user queries are being used to ask Gen-AI to come up with desired outputs. With every prompt, the query gets more defined, and the Gen-AI tools get even more sophisticated. In summary, DAM has a lot to gain from Gen-AI, as it stands to become from an asset management tool to a one-stop shop for content generation, collection, management, and storage. And it spells good news for organizations of all industries and sizes.