ABS-CBN faced a significant bottleneck in their content workflow. The manual process of tagging videos from TV Patrol, their flagship news program, was time-consuming, resource-intensive, and prone to human error. This created considerable delays in analytics, preventing the newsroom from extracting timely, actionable insights from their vast video library and hindering their ability to understand content performance quickly.

By developing and implementing a streamlined, automated tagging mechanism using AI, ABS-CBN successfully transformed its video processing and analytics capabilities. The experiment proved that AI could help with transcription, translation, and tag generation. This frees up journalists and editors to focus on core reporting and storytelling. More importantly, the consistently accurate and detailed tags enabled a richer, more granular level of data analysis, providing the newsroom with powerful insights to inform editorial strategy, optimize content for various platforms, and uncover new opportunities for repurposing archival material.