Authoritative, accurate, and authentic asset tagging is essential to the success of every DAM to ensure assets are easily discoverable and properly categorized. However, while crucial, tagging is tedious and time-consuming.
So, how can you amplify the time and effort your team invests in tagging with AI?

The key lies in understanding what AI technology actually does, what the output will look like, and how to effectively use that output.

Chief Product and Technology Officer Mohan Taylor demystifies the types of AI technology behind automated asset tagging. He covers traditional techniques like text recognition, along with the “bread and butter” of automated tagging—object detection, classification, and segmentation—and how to leverage image-to-text conversion and LLM-powered captioning to generate meaningful descriptions.

With a pragmatic perspective that inspires excitement, you’ll learn how to harness the outputs of these techniques to significantly enhance your asset ingestion, categorization, and organization, empowering your team to work more efficiently.

Key takeaways include: 

• Defining models, training, learning, and inference
• Types of AI technology behind automated asset tagging, with real-world examples from a global CPG brand
• Tips for combining AI techniques to improve content categorization, descriptions, and searchability
• How to train and fine-tune AI models using your DAM’s data 
• How to manage your expectations and succeed with automated tagging