Tempo de leitura: 4 minutos
Artificial Intelligence (or A.I. for intimates) is a term that, when mentioned in any context, draw the eyes of anyone. It started to be studied since the 50’s and has numerous definitions but the one that I found most suitable to the context of DAM platforms was this:
“Artificial intelligence is a system’s ability to correctly interpret external data, learn from that data and use that learning to achieve specific goals and tasks through flexible adaptation”Wikipedia, Artificial Intelligence
And, without realizing it, it has already invaded all spaces, all sectors and has been applied in countless purposes. For me, one of the most incredible is the application in IoT (Internet of Things) but that is the subject for another article.
In the same way that Artificial Intelligence helps several applications to automate repetitive learning and discovery from data, it adds intelligence in the context where it is inserted, adapts through progressive learning algorithms and achieves exceptional accuracy, the same occurs in platforms Digital Asset Management (DAM).
It is essential to accelerate and bring automation and quality to the process of managing and distributing digital assets at several points.
Let’s go to them:
Identification of characteristics of the digital asset
Through artificial intelligence, the platform can identify all the characteristics (attributes) inherent to digital assets (texts, images, videos, audios) that are being included in the platform DAM as predominant colors, objects, people, contexts, places, keywords, among many others. This facilitates the advanced search when you have a large volume of assets.
Digital Asset Categorization
This, perhaps, is the application of artificial intelligence that most brings performance to the process. Assuming that the I.A. automates repetitive learning, it starts to learn (*) with the way we categorize data according to the taxonomy structure created within the platform DAM, learning where and how items are classified within this taxonomy and automating this process, which, manually, is very time-consuming. The performance gain is clear mainly in large volumes of assets. Of course, it is always good to check, but the margin of error is minimal.
(*) This is what we call Machine Learning – Technology where computers have the ability to learn according to the expected responses through associations of different data, which can be images, numbers and everything that this technology can identify. That’s right!
Digital asset suggestion (Amazon Suggestion)
I mentioned the “Amazon Suggestion” which is easy to understand. From the moment you search for a digital asset, I.A. can be used to bring other digital assets with similar themes or attributes and related assets that other people have also looked for (just as Amazon does when you choose or buy a book). This can facilitate the user to create automated collections and shortcuts of related assets that are always used together and that also facilitates downloading or sharing.
I have a theory that if you include several files in a repository you want to find them easily and that is where the DAM platform most uses all the benefits of A.I. With the automated identification and classification of digital assets the search becomes a powerful tool to locate any asset of any format in any way you want. You can search for digital assets by an object, or predominant color, by a place or monument, by a person who has certain characteristics (ex: woman with glasses and a red dress) and the platform will bring you all digital assets, whether text, images, videos and / or audios that contain these sought-after characteristics.
Last but not least is to make use of artificial intelligence to make your DAM platform a tool (wait for my next post on this) using technologies to connect various features such as using bots on channels like WhatsApp and Telegram facilitating the search for assets through voice search. In this case, technology facilitates access to assets without users having to access the platform to search for assets. Excellent for field teams that usually have very limited internet and data package resources. This takes your platform to a “voice first” level and no longer “mobile first” where most DAM platforms are still adapting.
This is just the beginning. As I.A. advances it “commoditizes” its use making it accessible at all levels. At all times, new applications for DAM platforms appear. Before making your choice, check if your supplier can help you improve your digital asset management process. It will be essential to bring you performance and automation in long tasks.
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Havaianas case of Digital Asset Management (DAM) for Trade Marketing
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