Asset Authenticity
With the growing use of generative AI in marketing and, more precisely, content creation, marketing managers need more oversight and control over AI-generated content. Asset Authenticity is a capability that allows detection of AI-generated assets within the DAM and flags them for awareness. As the use of Generative AI grows, this feature ensures that users have full transparency over the origin of assets stored in their libraries, promoting trust and accountability in content management.
Implementation in DAM systems
For DAM users, Asset Authenticity provides several key benefits by enabling transparency and control over their content creation. This capability ensures users can differentiate between human-created and AI-generated content, helping them maintain control over asset usage. It also enables users to safeguard their brand by using only approved and on-brand content in their marketing campaigns. Additionally, it supports regulatory and internal compliance requirements by providing clear visibility into asset origins, ensuring adherence to ethical AI practices, and reducing the potential risk of reputational damage or legal challenges associated with unverified or unauthorized use of AI-generated content.
What is the technology behind it?
Asset Authenticity often uses specialized algorithms – like convolutional neural networks (CNNs) – to detect patterns (or “fingerprints”) that set AI-generated content apart from human-made assets. CNNs excel at finding pixel-level artifacts or inconsistencies that generative models used to leave behind. By analyzing these visual hints as soon as a new asset is uploaded to the DAM, the system can accurately determine if the item was created by an AI model.
