Objectives:
This project aims to explore how agentic AI can be applied across the full live media value chain, from production through to distribution and consumption.
It will focus on orchestrating multiple AI-driven capabilities, including real-time content understanding, automated production tasks, highlight generation, localisation, personalisation, and monetisation.
The objective is to move beyond isolated AI use cases and demonstrate how coordinated, end-to-end workflows can transform live content into dynamic, multi-platform, and personalised experiences.
This includes enabling “Me-Cast” scenarios, where content is continuously adapted to individual viewers, while remaining grounded in practical production and delivery environments.
Innovation and Collaboration:
Across the industry, AI has largely been applied in isolated use cases, often as standalone tools within either production or distribution workflows. Meanwhile, live media operations remain complex, manual, and siloed, limiting the ability to fully leverage real-time content. There is a need to move towards integrated, agentic approaches that operate across both production and distribution, enabling content to be created, adapted, and delivered as part of a continuous, intelligent workflow.
This includes applying AI within production to automate and augment tasks such as logging, segmentation, highlight creation, and editorial assistance, while simultaneously enabling downstream capabilities such as localisation, personalisation, audience engagement, and targeted monetisation. These capabilities must be orchestrated together, allowing content to flow seamlessly from live production into multiple tailored outputs in real time. These approaches will then be tested within production and distribution environments to understand how they can be applied in practice at scale.
Broadcasters and content owners will define production workflows, editorial requirements, and rights constraints, technology partners will contribute agentic systems and AI capabilities across the chain, and platform partners will support distribution, engagement, and monetisation models. Working together enables the development and validation of end-to-end, multi-agent workflows that are both operationally viable and scalable across the industry.