{"id":1994,"date":"2024-11-08T10:15:18","date_gmt":"2024-11-08T10:15:18","guid":{"rendered":"https:\/\/gyrus.ai\/blog\/?p=1994"},"modified":"2024-11-08T10:43:24","modified_gmt":"2024-11-08T10:43:24","slug":"role-of-ai-enabled-media-asset-management-in-efficient-content-handling","status":"publish","type":"post","link":"https:\/\/gyrus.ai\/blog\/role-of-ai-enabled-media-asset-management-in-efficient-content-handling\/","title":{"rendered":"The Role of AI-Enabled Media Asset Management in Efficient Content Handling"},"content":{"rendered":"

Content is the king in today\u2019s digital media world, however, the management of video content at scale can be overwhelming. AI Video Streaming<\/a> services, broadcasters, advertisers, and media companies are required to handle thousands of video assets on a daily basis.<\/span><\/p>\n

AI-Enabled Media Asset Management (MAM) is the answer – a next-generation solution that transforms vast video libraries into meaningful insights. This technology helps to make content search-friendly, automate workflows, and inform for ease in decision-making.<\/span><\/p>\n

In this blog, we will consider how AI-enabled media asset management is key to optimizing content and making it easier, quicker, and more efficient to manage vast video libraries.<\/span><\/p>\n

What Is Media Asset Management (MAM)?<\/strong><\/h3>\n

Media asset management is the process of storing, organizing, and retrieving digital video and media files. It includes creating metadata tags, indexing, archiving, and\u00a0 managing workflows. As more and more video content is created, a traditional MAM system just can’t keep up with the amount of footage generated, resulting in inefficiencies and wasted time.<\/span><\/p>\n

This part has been completely changed by AI. MAM systems can now automatically analyze video content using AI and deliver meaningful metadata. This makes it easy to look through large amounts of data and take desired actions.<\/span><\/p>\n

The Need for AI in Media Asset management<\/strong><\/h3>\n

\"\"<\/p>\n

As content is becoming more personalized, video optimization across platforms, audiences, and formats has never been more important. Here is why AI is so critical.<\/span><\/p>\n

Long Processes Time: <\/strong>Tagging and categorizing video is labor-intensive, which can be a lengthy manual process without AI.<\/span><\/p>\n

Poor Metadata Management:<\/strong> <\/span>Manual tagging is not effective, especially when detail might be overlooked or misunderstood, and hence, it becomes difficult to search and re-use video content effectively.<\/span><\/p>\n

Missed Monetization Opportunities: <\/strong>Unable to personalize and deliver targeted ads or improve the engagement of users without accurate content insights.<\/span><\/p>\n

AI embedded in MAM systems helps to alleviate these challenges by automating several tasks, improving searching options, and providing actionable insights.<\/span><\/p>\n

Key Benefits of AI-Enabled MAM in Content Management<\/strong><\/h3>\n

With AI-integrated media asset management, companies can make decisions that are data-driven regarding their infinite video assets. Here are the key benefits:<\/span><\/p>\n

\"\"<\/p>\n

1. Enhanced Searchability:<\/strong><\/span><\/strong><\/p>\n

With AI-driven metadata tagging, you can instantly search for the object, person, or word depending on what matches and is relevant to a scene. It takes less time to find relevant video clips, so it improves efficiency.<\/span><\/p>\n

2. Automation of Tedious Tasks: <\/strong><\/p>\n

Automating video tagging, transcription, and facial recognition are some examples of tasks AI handles. This greatly decreases manpower and operational costs.<\/span><\/p>\n

3. Improved Content Discovery:<\/strong><\/p>\n

Build personalized target audiences to adjust video recommendations using AI This works to optimize content as per individual viewers, which results in increased user retention and engagement.<\/span><\/p>\n

4. Scalability:<\/strong><\/p>\n

AI makes it possible for MAM systems to handle very large video libraries and repositories. This makes sure that content can always be easily accessed, no matter how vast it is.<\/span><\/p>\n

Use Cases of AI-Enabled MAM in Different Industries:<\/strong><\/h3>\n

\"\"<\/p>\n

Over the past few years, AI has been implemented in modern MAM systems and revolutionised video content for just about every industry. Here are a few examples:<\/span><\/p>\n

Broadcast and Streaming Services: <\/strong>AI empowers broadcasters to manage and monetize massive video libraries by supporting precise search, accelerated content retrieval, and tag videos automatically for genres, people, and things.<\/span><\/p>\n

Marketing and Advertising:<\/strong> <\/span>AI-driven MAM systems assist in contextually adding advertisements by understanding the video content for marketers. For example, in-scene advertising can deploy virtual banners on a given video frame using AI.<\/span><\/p>\n

Film Production: <\/strong>AI accelerates the post-production process by automatically indexing scenes, generating a transcript, and detecting objects to help editors more easily locate and use specific clips.<\/span><\/p>\n

Best Practices for Implementing AI-Enabled MAM<\/strong><\/h3>\n

\"\"<\/p>\n

Here are some best practices to follow for businesses\/companies that are planning to implement AI-enabled MAM solutions<\/strong>.\u00a0<\/span><\/p>\n

Opt for a scalable system:<\/strong> <\/span>Select a system that scales based on your level of video content and easily integrates AI-driven tools.<\/span><\/p>\n

Use Cloud Technology:<\/strong> When it comes to using cloud-based MAM systems, they ensure that video archives can be accessed faster and more efficiently from anywhere.<\/span><\/p>\n

Invest in customized AI models:<\/strong> Invest in custom AI models based on your requirements. Whether it\u2019s for content tagging, video anonymization<\/a>, or personalized recommendations.<\/span><\/p>\n

Partner with Data Scientists:<\/strong> <\/span>Engage AI and machine learning professionals to confirm that the AI models used in your MAM system are suitable for both their intended purpose(s) and execution.<\/span><\/p>\n

AI automates tasks that can be repetitive, and it provides smart search functionalities, so you get to focus on what really matters\u2014by building high-quality content.<\/span><\/p>\n

How Gyrus AI\u2019s Media Search Solution Augments Media Asset Management?<\/strong><\/h3>\n

\"\"<\/p>\n

The first step involves an AI vision model<\/a> looking over the visual content of a video and creating text descriptions that are meaningful to the context with each scene or frame. Simultaneously, a separate AI audio model processes all your spoken content and creates automated speaker-extracted transcripts. The descriptions and transcripts are analyzed to create specific time ranges for specific events or moments in the video.<\/span><\/p>\n

The video and audio data, once processed by the system, get attributed with relevant tags for each timestamp to build comprehensive metadata (like events) of all this. It is then used to create a knowledge graph, which uses relationships between different pieces of information. These knowledge graphs facilitate expanding the search function by linking data to public ontologies\u2014external databases that provide additional context.<\/span><\/p>\n

These information’s are then compiled into a search interface that makes it easy to rapidly and accurately find the content based on keywords, objects, people, or events within the video. It streamlines the entire workflow for faster content retrieval and discovering valuable insights from large video repositories.<\/span><\/p>\n

GYRUS AI<\/a> provides custom AI models for Media Asset Management Search (MAMS). Built for your use case, be it as a broadcaster, advertiser, or media creator, our solutions are tailored to achieve what you require.<\/span><\/p>\n

To learn more about how our AI technologies can help your video content perform better, you may contact us at info@gyrus.ai<\/a> or simply click here: <\/span>www.gyrus.ai<\/span><\/a>\u00a0<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"

Content is the king in today\u2019s digital media world, however, the management of video content at … The Role of AI-Enabled Media Asset Management in Efficient Content Handling<\/span>Read more<\/a><\/p>\n","protected":false},"author":11,"featured_media":1996,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"categories":[6],"tags":[111,119,96,120,122,121,90],"class_list":["post-1994","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-technology","tag-ai-technology","tag-ai-video-streaming","tag-ai-vision-models","tag-ai-ml-techniques","tag-mam-solutions","tag-media-asset-management","tag-video-anonymization"],"yoast_head":"\nAI-Enabled Media Asset Management in Efficient Content Handling<\/title>\n<meta name=\"description\" content=\"GYRUS AI provides custom AI models for Media Asset Management Search (MAMS). 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