Connecting the editorial context

Newsrooms have never been short of information. The challenge has always been making sense of it quickly, accurately and creatively, particularly when a major story is breaking and changing by the minute. 

Today, the systems supporting news production are highly capable, but they often operate in isolation. The rundown system, media asset management platform, graphics tools and planning applications may all contain pieces of the same story, yet they do not necessarily share a common understanding of its editorial context. Media Object Server (MOS) has played an important role in connecting these systems operationally. What is still missing is a layer that connects them editorially.

That gap is at the heart of this year’s IBC Accelerator Incubator project, “Smart Stories: The New Knowledge Architecture for Content Production.” The project, which Moments Lab is proud to be part of, is focused on defining an open standard for story context interoperability in news production through the development of a Story Object Model (SOM).

The idea is straightforward but potentially transformative: Give the systems and AI agents involved in the entire production chain a shared understanding of what a story is, what is happening, what has changed and what matters. Rather than requiring news producers to repeatedly re-enter information, interpret incomplete metadata or correct misunderstandings between tools, the story itself becomes the organizing context that travels through the workflow.

This is increasingly important as news production becomes more complex. A single story may result in live updates, web articles, broadcast packages, social clips, alerts, graphics and audience-specific versions across multiple platforms. For news organizations, particularly the digital, social and archive teams working beyond the linear broadcast stack, the challenge is not simply creating more output. It is finding, repurposing and publishing the right content quickly enough to serve audiences across the channels where they now consume news.

Each output may involve different teams, systems and editorial decisions. Without a shared context, valuable time is spent transferring information between interfaces instead of developing the story and applying editorial judgment. Archives that could support coverage, provide context or generate new digital revenue can remain difficult to search and slow to activate.

Agentic technology with people in control

Agentic technologies can help address this problem, but newsrooms are not generic automation environments. They are dynamic, collaborative and subject to serious editorial, legal and ethical responsibilities. When a story breaks, people and systems must respond rapidly to new facts, conflicting information and changing priorities.

Any agentic workflow must therefore do more than automate tasks while keeping humans firmly in the loop. It must understand where content belongs, how it relates to an evolving story and how to complement the skills of the people who retain editorial and publishing control.

This project addresses a foundational challenge. It is not simply a proof of concept designed to demonstrate what technology can do in isolation. It brings together an exceptionally broad group of organizations to examine how an agentic workflow could operate across the real news production chain.

An industry-wide approach

The project blueprint was written by Alex Bassett at NBCUniversal, Morag McIntosh at the BBC and Jon Roberts, CTO at ITN. Brian Hopman at AP is project co-lead. Other project champions include Al Jazeera, Washington Post, Channel 4, ITV, Sky, EBU, SMPTE, Reuters, Scripps and The Global Creative & Security Community. The participating vendors and technology organizations alongside Moments Lab are Shure, EVS, CUEZ, Fonn Group, Perspective Media Group, Google Cloud, TRINT, Cognizant, Nuvelics, AWS, Octopus, The Weather Company, HyperContent AI, LiveU and Electric Sheep.

That breadth matters because no two newsrooms are organized in exactly the same way. Each has its own combination of planning tools, media systems, editing platforms, graphics environments, archive structures and publishing workflows. Many of those tools come from different vendors, with areas of overlap and varying degrees of integration. Yet, across that complexity, the underlying challenges are often shared.

We are bringing our collective experience of working with newsrooms to this project, looking at what has worked well in MOS, what we learned from last year’s award-winning IBC Accelerator project, “AI Agent Assistants for Live Production,” and which elements genuinely changed the workflow. We are also examining the challenges that are specific to each organization and production environment.

The goal is not to prescribe one set solution or produce another isolated proof of concept. It is to ask how the industry can respond to this technological inflection point in a way that enhances news production while preserving the qualities that make newsrooms successful: editorial judgment, collaboration, creativity, accuracy and the ability to respond under pressure.

From breaking news to the archive

At Moments Lab, our contribution focuses on two connected workflows. A Discovery Agent can suggest relevant archive content when a story first breaks or as it develops. Our MXT multimodal AI indexing technology can also identify how newly ingested content relates to existing news stories, helping prevent material from being incorrectly tagged or lost.

This creates a practical bridge between the live story and the archive. As soon as a breaking story lands on the newswire, related moments that exist in the archive are already available for editorial curation. This enables news teams to focus on telling the new parts of the story rather than hunting for old B-roll.

Teams can easily surface relevant footage, repurpose it for broadcast, web and social audiences and continue working within the systems and editorial processes they already rely on. Moments Lab’s work with ITN and 5 News offers a real-world example of this direction, using AI to make a large news archive and new daily content easier to discover and put to work.

The aim is not to replace the newsroom’s existing infrastructure, but to make its content more discoverable, portable and useful across nonlinear distribution. Once that content and context are published to the SOM bus, other tools and teams can act on it without requiring people to move files manually, switch between multiple interfaces or send additional alerts.

This aligns with Moments Lab’s broader focus on AI video discovery, management and creation that enhances other systems and workflows as seamlessly as possible.

Rather than seeking to remove the human element from journalism, we want to give journalists and producers better support, so they can spend less time managing fragmented systems and more time making informed editorial and creative decisions.

A foundation for the future newsroom

The most exciting part of this work is that we are helping shape a potential foundation for future news production. Creating a shared story context standard at this stage is challenging, particularly at the scale and with the number of organizations involved. But it is also a rare opportunity to address a structural problem before another layer of disconnected integrations becomes entrenched.

The future newsroom will not be defined by one AI tool or one vendor. It will depend on many specialized systems working together intelligently, transparently and responsibly. For that to happen, they need to understand the same story. SOM could provide the common language that makes that future possible.

Learn more about this project and how the Moments Lab platform helps broadcasters centralize, index, discover and share video content at scale at IBC Show, Sept. 11-14, 2026, in Amsterdam. Book a meeting.