AI and GenAI based Media Asset Management

The role of AI in DAM becomes a game-changer in reducing the time spent on manually sorting and categorising assets in the digital space. It can automatically analyse vast amounts of content.

The advent of artificial intelligence has guided the transformation of the digital landscape. With more technological development comes an increased inflow of data, creating a need for more strategic initiatives towards data management and utilisation. Digital Asset Management (or DAM) is an organisation's process for effectively handling its digital assets by focusing on efficiency and discoverability. DAM helps organise datasets in a unified system, making them more accessible for teams. Such centralisation also helps set up appropriate data governance processes for specific access controls, allowing only limited individuals to access such material, making it less prone to data leaks.

The advantages of an AI-based asset management system are numerous. For one, such a system helps streamline workflows by deploying appropriate process automation systems (e.g., RPA) and increasing productivity in the organisation, enabling organisations to be strategic in their data management efforts. It also helps manage digital rights, enhance the search and retrieval of media assets, and further categorise media content. Now with the addition of generative AI, it can be further leveraged for effectively utilising these assets at scale across the organisation for many cross-functional requirements. For example, business process optimisation, sales process streamlining, inventory management, contract management process and so on.

Creating Metadata Tags

The role of AI in DAM becomes a game-changer in reducing the time spent on manually sorting and categorising assets in the digital space. With AI algorithms with multi-modal capability, it can automatically analyse vast amounts of content, such as images, voice, audio and rich media content. With AI / GenAI tagging becoming more efficient and significantly error-free, we can see it can be well over 95%. Through specific tags, Gen/AI makes it easier to identify digital assets through specific keywords that become automatically associated with them.

One of the most important things about AI is its capability to contextually understand media content, generating tags based on the themes and emotions conveyed in the media alongside the content explicitly present. For instance, along with identifying objects and people in a video, AI helps decipher the mood depicted, such as happiness in a moment of celebration or fear during a tense situation. Machine learning algorithms trained on vast datasets can recognise patterns and associations to generate specific tags across diverse media, like the genre of a specific music clip or the art style of a particular image, making it easier for identification and categorisation. These high-definition metadata are becoming the key ingredient for additional monetisation and revenue opportunities for all the players in the media value chain.

Managing Digital Rights

AI plays a crucial role in managing digital rights as well. Digital rights are closely associated with human and legal rights allowing individuals to access, use, create, and publish digital media or even use telecommunications networks. Digital rights are crucial for all key media we publish in today's fast-paced world. AI helps detect unauthorised use and ensures compliance with licensing agreements by recovering the signature at the appropriate stage. For instance, AI tools can monitor the usage of digital content to ensure it complies with the terms of licensing agreements. This includes tracking how, where, and by whom the content is being used.

Additionally, It is now possible to add digital signatures to the content at various stages of content processing very transparently. AI algorithms can automatically scan and analyse digital content across various platforms to identify copyrighted material. This helps in detecting unauthorised use of content quickly and accurately, ensuring that creators and rights holders are alerted to potential infringements. AI tools can also help reduce the administrative burden on rights holders by automating the generation of detailed reports on content usage. As a predictive tool, AI can analyse patterns and trends in digital content usage to predict potential risks of unauthorised use or breaches, including licensing agreements.

Generative AI for Meta Data Generation

AI becomes pivotal in the utilisation of GenAI Model LLMs and other Generative AI tools to enhance the search and retrieval of media assets. GenAI Model LLMs are now used to understand the context and semantics of search queries, rather than just matching keywords, leading to more accurate search results. Additionally, Multimodal LLMs like OpenAI Sora, Google Gemini Pro, Microsoft LLaVa can process media content, such as audio, video, and text, to automatically generate descriptive metadata to enhance the searchability of media assets and make it easier to locate specific content.

Another advantage of the GenAI model is the creation of sophisticated recommendation systems that suggest relevant media based on user preferences and previous interactions. It further helps with personalisation as a powered system can process and understand multiple languages, enabling search systems to handle queries and retrieve media assets in various languages. The key benefit of the GENAI model for AI is paving the way for users to discover valuable media that might otherwise remain buried in large libraries. Thus, AI and GENAI models significantly enhance the search and retrieval processes for media assets, leading to more efficient, accurate, and user-friendly media management systems.

AI and the Way Forward

AI-based media asset management represents a transformative leap in how organisations handle their vast collections of media content. By leveraging the power of Gen AI technologies such as natural language processing, automated content recognition, and predictive analytics, Gen AI-based systems enhance search accuracy, streamline metadata generation, ensure compliance with licensing agreements, and provide robust digital rights management.

These advancements not only improve the efficiency and effectiveness of media asset retrieval and management but also enable a more personalised and engaging user experience. As Gen AI continues to evolve, its integration into media asset management systems promises to unlock new possibilities for creativity, collaboration, and innovation in the media industry. To conclude, AI is a powerful tool in the digital realm that can be wielded to create, ease, and protect our digital assets.

Author: Biswajit Biswas, Chief Data Scientist, Tata Elxsi