Artificial Intelligence has been used in Digital Asset Management for a while. In this article, we explained how AI facilitates DAM.
Not long ago, artificial intelligence (AI) technology was just the concept of science fiction movies. But today, AI is changing the status quo for the entire industry, including marketing technology (martech).
In the field of marketing, AI features are increasingly being used in Martech tools. Leverage the automation features used to enhance chatbots, personalize content, and even manage social media platforms.
As consumer expectations change and agile and disruptive retailers enter the ecosystem, marketers need to be able to compete to attract consumer attention across more and more channels. For these marketing teams, this means ensuring that the visuals used are accurate and compelling enough to turn consumers into paid customers in highly competitive situations.
One way for companies to optimize their content strategies to enable AI is to use Digital Asset Management (DAM), which helps marketing teams organize, search, distribute, and analyze digital content. Now that AI capabilities are on the rise, how can you use AI to streamline your DAM workflow?
Image Recognition
To be effective, the DAM software program is predicated on metadata or descriptive records for approximately every piece of content material to offer the shape and records to make virtual belongings discoverable. Metadata is vital to the fulfillment of your machine, however including metadata is frequently time eating and error-inclined without a well-described process.
When operating with metadata, fields are used to reply to specific questions on every asset, inclusive of filenames, image types, descriptions, identifiers inclusive of utilization rights, and so on. The machine of metadata fields is referred to as the metadata schema.
Creating a schema that consists of fields that can be applicable to a selected enterprise will enhance your seek enjoyment and make sure that metadata is brought accurately. And with the assistance of photo popularity software programs, AI has a precious and developing function in machine control via its capacity to robotically tag belongings with applicable metadata all through the add process.
Upsides of Image Recognition
Creates Accuracy:
Using Artificial Intelligence to automate part of the image tagging process improves classification, improves the accuracy of related assets, and provides users with advanced search options. Not to mention saving time on manual tagging tasks.
The ability to automatically classify and tag images is extended to a variety of scenarios. You can recognize a person’s face and demographics (age, ethnicity, gender, etc.) in the image. You can also apply keywords to specific industries such as travel, groceries, and apparel. Adding image recognition capabilities to your
DAM system makes it easier, faster, and most importantly, better at creating metadata. Image recognition software can reduce human error and inconsistencies and prevent assets without metadata from being uploaded to the DAM system.
In addition, AI can make your search more effective because the search tool can quickly provide accurate results with complete metadata.
Saves Time:
Not only can AI create accurate content, but marketers can ultimately save more time on repair and security-related tasks, discover anomalies, and report potential bugs. Image recognition software includes features that allow Digital Asset Management administrators to:
- Digital transformation calls for worker advice
- Moderate property and routinely take away or disguise uploads that comprise beside-the-point content.
- Enables the automated tagging characteristic for precise add profiles or metadata fields.
- Affects how strength, relevance, and various controls are configured.
Automating manual processes reduces the time it takes to tag assets. In other words, you can streamline your workflow. All of these efficiencies lead to cost savings for the enterprise. After all, less tagging and searching means spending more time on creative and strategic work.
Bias About AI in Digital Asset Management
Over the past few months, we’ve seen some examples of AI being labeled as “biased”. Recently, Twitter has been accused because of the fact that they have biased artificial intelligence image cropping algorithms. To avoid such negative headlines, the tech giant has announced that it will discontinue image cropping software and allow users to crop images at their discretion.
Such negative headlines are regularly featured in the media, making marketers truly adopt AI in their workflow processes for fear of becoming victims of “biased AI” and leading to a public relations crisis. There is no doubt that there is a risk of being too afraid of things.
However, there is one way to prevent businesses from becoming victims of such deaths. Marketers and developers need to fully understand not only the data being used but also the patterns that the data creates. In this way, you can take advantage of AI tools to effectively and efficiently automate system management for your marketing team.
Ultimately, it’s not the technology of artificial intelligence that’s biased, but the algorithms developed by a team of humans.
Looking to the Future of AI and Digital Asset Management
Despite some concerns, it is undeniable that we are actually moving into a digitally converted online world. However, while technology has helped many companies operate more efficiently and quickly, it is also clear that this cannot be achieved without human intervention.
Technology alone cannot modify an organization’s operations. People, processes, and technologies like AI need to be coordinated to develop strategies to achieve the desired marketing outcomes.
Tools like image recognition need a balance between automation and human touch. You can free up time and resources for other value-based projects, but still, people to ensure the accuracy of all data entry and inform and guide both the technology and its users. Resources are needed.
As we monitor further developments in this area, we find that the partnership between AI and the human workforce becomes increasingly important to marketing teams. Not only to streamline and extend your Digital Asset Management workflow, but also to successfully reduce costs.
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