Industry
Publishers, broadcasters, streaming and gaming companies: content operations, personalization and audience service.
31 organizations in 13 countries run these use cases in public. 45% of those 31 deployments disclose a measurable outcome.
An AI agent for sports highlights and clipping watches a live sports broadcast and detects key moments such as goals, saves or penalties as they happen. It automatically extracts and reformats a clip and puts it in front of an editor to review and publish, instead of a person watching every feed and clipping moments by hand.
A publisher archive answer engine is a generative AI search and answer tool on a publisher's site or app that answers readers' questions from its own journalism. It answers only from that publisher's published journalism and archive, cites the articles it used, and declines to answer when its own reporting does not cover the question.
AI content moderation for trust and safety scans user generated content, such as live video, images, chat and audio, against an online platform's policy in real time. It removes or hides the clearest violations and routes borderline cases to a human moderator with its reasoning attached, so the platform can review far more content than a human team alone while keeping irreversible decisions with a person.
AI live sports commentary turns a sporting event's own data into written commentary and insight for fans as the action happens, instead of or alongside a human broadcaster. It works from inputs such as ball and player tracking, match events and statistics, and can optionally use text to speech to voice the output for a spoken version.
AI marketing personalization at scale is AI that decides, for each customer, which product, offer, message or content to show next, for a marketing team running many campaigns. It works across email, app, web and paid media, and generates the matching copy and creative variants within brand and compliance rules. It is the team's engine across many campaigns and channels, not an agent that converses with the customer.
AI media archive metadata tagging watches and listens to a broadcaster's or publisher's video and audio archive and generates structured metadata describing what is in each piece of content. It captures detail such as what is shown, who appears, spoken content, on screen text, logos and objects, so content makers can find and reuse footage through natural language search instead of relying on sparse, inconsistent tags added by hand over decades.
AI content recommendation and personalization decides what to show each viewer or listener next on a home page, in search or in a personalized playlist. It learns from that person's own viewing or listening history, ratings and context, updates continuously as new content is added and behavior changes, and ranks only the catalog's own content, not marketing offers or campaigns.
AI transcription and captioning is AI that transcribes recorded audio and video, such as podcasts, broadcasts, lessons, interviews and hearings, in several languages. It separates the speakers and produces timed transcripts, subtitles and captions for a human editor to check, delivered as files for publishing or the archive.
An AI visitor and tour guide tells visitors of cities, museums, heritage sites and events the stories behind what is around them, and answers their questions in their own language. It is often spoken, location and context aware, grounded in the organization's curated content and in the visitor's position or the object they scan.
Free PDF playbook
9 use cases with deployments, value, playbooks and governance, in one document for your team.
Computed from the 31 public deployments behind these use cases at media and entertainment organizations. Numbers update with every checked record.
12 public deployments at 12 organizations outside media and entertainment run these use cases too. They are not counted in the numbers above; each use case page shows them.
