Manual digital asset management is an unforgiving process in which employees spend hours manually tagging creative assets so that other users can discover them. When working with hundreds or thousands of assets, the workload is too much for human-users to manage alone.
The only efficient and sustainable way to manage rich media assets is with automated tagging of metadata. To do this, you need business-specific artificial intelligence (AI). The Nuxeo Platform is ideal for this because it enables marketing teams to work alongside machines that tackle mundane administrative tasks while humans handle creative tasks.
Generic vs Business-Specific AI
The Nuxeo team has found two ways that companies can use AI to enhance, enrich, and optimize their DAM processes:
- Generic AI - Connect to a broad range of public AI services for common use cases where commodity ML models provide generic services. Generic AI includes tasks like general classification, enrichment, OCR, speech-to-text, etc.
- Business-specific AI - Train machine learning models on your own content and data to get highly relevant insights and enrichments that enable specific business use cases across defined domains. Custom models deliver more meaningful business outcomes.
Both types of AI help product companies in different ways but excel when they’re combined.
Combining generic and business-specific AI together gives you the option to automate basic manual tasks while gathering more sophisticated insights. Generic AI acts as the foundation of your digital asset management process, and business-specific AI enables you to tune content/data collection results to your needs.
In isolation, generic AI can be incredibly useful for automating repetitive tasks like transcribing speech into written documents or classifying documents. In these scenarios, AI increases efficiency by speeding up the completion of time-consuming manual tasks.
However, generic AI falls flat when it comes to gathering more in-depth insights and managing rich media assets. For example, in a retail environment, generic AI may be able to identify and tag the main product displayed in an image but will struggle to recognize other accessories shown in the image.
When you want to manage rich media assets and gather more in-depth insights, business-specific AI is superior. Business-specific AI built by custom ML models can automatically tag rich media assets and provide the user with more in-depth contextual information on an asset.
For instance, Nuxeo Insight can analyze your data to classify, predict, and enrich media assets independent of a human-user. It can link assets or designs to contracts, digital rights, materials libraries, and sales information. By providing more contextual information, Nuxeo unifies the digital supply chain by delivering content in context for upstream and downstream teams.
The Rise of Co-Bots and Collaborative Intelligence
Manual tagging is a key pain point of many companies using DAM solutions. In most companies with DAM systems, employees need to go through thousands of images and to add tags to these assets so that they can be found by other individuals later on.
Unfortunately, the process isn’t scalable, and these human users are put under tremendous stress trying to add dozens of tags to thousands of images. The lack of scalability results in inconsistent and inaccurate tags, making it more difficult for other users to find creative assets when searching through a DAM solution.
The process wastes time and often results in media assets being lost or forgotten during critical campaigns. However, the growth of AI has ushered in the rise of co-bots and collaborative intelligence, where machines work alongside human-users to automate tedious manual tasks while humans focus on creative tasks like branding.
By working together, humans and machines make an effective team where employees can automate undesirable, monotonous, and time-consuming tasks. AI doesn’t replace humans but works alongside them to produce a more efficient and happier workspace.
The Future is Collaborative
The era of manual digital asset management is coming to an end. Forcing employees to try and tag thousands of images with manual tagging alone isn’t a sustainable solution for managing creative content. Enabling employees to collaborate with AI is a must-have for maximizing efficiency. By automating tasks like manual tagging, AI reduces the workload of employees so that they have time to focus on other tasks.
Next-generation DAM systems like the Nuxeo Platform will enable you to create a comprehensive repository of content tagged with the right key terms. Increased tagging accuracy ensures your creative team can find what they need to make the next groundbreaking product.
If you want to learn more about how Nuxeo’s AI can save your Digital Asset Management users, check out this report Reducing Image Hide & Seek with Artificial Intelligence.