Wimbledon (The Championships)
editorial content generated by genAI in the brand voice for fan engagement
Wimbledon uses IBM watsonx.ai to generate player summaries (Catch Me Up) and audio commentary on highlights in the tournament's editorial tone: in 2025 the AELTC reports a 16 percent rise in engagement across all platforms and 39 percent growth in myWIMBLEDON registrations.
Key points
- Catch Me Up player summaries and audio commentary on highlights generated by AI.
- IBM watsonx.ai and watsonx.data, model tuned on the tournament's editorial tone.
- Plus 16 percent engagement across all platforms and plus 39 percent myWIMBLEDON registrations in 2025.
- Evidence level B, confirmed active status.
Objective
Retain and deepen the engagement of a global audience during and around the tournament by delivering personalized content and automatically generated narratives, without expanding the editorial team for every match.
The deployment
On the Wimbledon app and on wimbledon.com, the Catch Me Up feature generates summaries for each singles player: what happened in their last match and what is at stake in the next. The fan personalizes their list by adding favorite players. Fans can also add AI-generated audio commentary to highlight reels, with narration at the start and end of the reel and on key points. The content is produced by IBM watsonx.ai, a model tuned on trusted Wimbledon data and trained to write in the tournament's editorial style and tone. Structured and unstructured data are managed by watsonx.data on an open lakehouse architecture, accessible to applications across the club's hybrid cloud. These capabilities add to the Likelihood to Win feature, which continuously computes each player's probability of winning.
Results Proof B
Quantified platform case study (IBM watsonx), corroborated by an IBM/AELTC press release and by the business press (Fortune), which name Wimbledon and the engagement gains reported by the AELTC. Engagement figures reported by the brand through its partner, hence B rather than A.
How it works
Documented architectureThe stack in detail
- plateforme IBM watsonx.ai Generates the Catch Me Up summaries and the highlight audio commentary, with a model tuned on Wimbledon's data and editorial tone.
- infra IBM watsonx.data Open lakehouse that manages the tournament's structured and unstructured data, accessible to applications via the club's hybrid cloud.
- integrateur IBM Consulting Operates the model and supports editorial oversight alongside the AELTC digital team.
- outil Application Wimbledon et wimbledon.com Distribution surfaces for the personalized summaries and audio commentary to fans.
How it runs, concretely
For ops teams-
1Match data ingestion data team / IBM
watsonx.data centralizes structured and unstructured tournament data on an open lakehouse architecture.
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2Content generation AI (watsonx.ai)
watsonx.ai, tuned on Wimbledon data and tone, writes the Catch Me Up summaries and the highlight narration.
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3Editorial oversight AELTC editorial team
The editorial team validates adherence to the style and factual accuracy before publication.
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4Personalized distribution site_app
The fan receives their summaries based on the players followed, on the app and the site.
Structured match data and Wimbledon history. If the supply of trusted data or the tuning on the editorial tone is missing, the generated content drifts from the brand style or produces factual errors.
How your customers perceive this type of use
Sourced studiesUn ecart net separe les annonceurs des consommateurs : 77% des annonceurs voient l'IA positivement contre 38% des consommateurs (Yahoo/Publicis, 2024). Les mesures implicites confirment le rejet declare : en EEG, les pubs generees par IA produisent une activation memorielle plus faible que les pubs traditionnelles et sont decrites comme agacantes, ennuyeuses et confuses (NIQ, 2024). La disclosure a un effet ambivalent : elle augmente fortement la confiance quand elle est remarquee (Yahoo/Publicis), mais 27% des jeunes consommateurs disent faire moins confiance a une entreprise dont la pub est creee par IA (IAB, 2024).
Acceptance conditions
- Une disclosure visible : quand la mention IA est remarquee, la confiance globale envers l'entreprise augmente de 96% (Yahoo/Publicis 2024)
- Une qualite visuelle suffisante : les visuels IA de basse qualite augmentent l'effort cognitif et distraient du message (NIQ 2024)
Red lines
- Le contenu IA non declare puis identifie : 72% des consommateurs disent que l'IA rend l'authenticite difficile a etablir (Yahoo/Publicis 2024) et les marques utilisant des pubs IA sont plus souvent jugees inauthentiques ou non ethiques par les consommateurs que par les dirigeants (IAB 2024)
- Les mannequins et personnes generes par IA : 46% des consommateurs n'en veulent pas dans la publicite, l'inquietude premiere etant les standards de beaute irrealistes (Attest 2025)
Sources: Yahoo / Publicis Media (terrain Ebco) 2024 · IAB (avec Attest) 2024 · NIQ (NielsenIQ) 2024 · Attest 2025
How to replicate
Inference, not sourcedData prerequisites
- reliable structured event data feed
- reference editorial corpus for the brand tone
- user identifier for personalization
Org prerequisites
- editorial team to supervise the generated content
- model governance and audience disclosure about AI content
- peak-capacity operations during the event
Possible stack
- genAI platform (watsonx, Azure OpenAI, Vertex AI, or equivalent)
- lakehouse / data store
- app or site with a personalization layer
The plan, step by step
- Step 1Build the reference editorial corpus (brand tone) and connect the structured event data feed.Deliverable: Editorial corpus + validated data feed.
- Step 2Tune or prompt the model on the house tone and generate summaries in house.Deliverable: Generator evaluated by the editorial team on real cases.
- Step 3Put human review in place before any distribution, with a fast loop during the event.Deliverable: Editorial validation workflow sustainable at peak.
- Step 4Open the beta to part of the audience (app).Deliverable: Live personalized summaries with engagement measurement.
- Step 5Draw the post-event review and extend (audio, finer personalization).Deliverable: Engagement and registration readout + roadmap for the next edition.
First step: Build a reference editorial corpus and connect an event data feed, then generate summaries with human review before any automatic distribution.
The same pattern, proven in other industries
Allstate
genAI drafting of customer communications with human review
Google for Education
genAI assistant integrated into an institutional education suite, admin-managed
Spotify
genAI voice DJ (synthetic voice plus generated commentary)
Sources
- S1 How IBM helps Wimbledon use generative AI to drive personalised fan engagement Interested party archive pending
- S2 Wimbledon and IBM Introduce New AI-Powered Fan Experiences and Modernized Digital Platforms for The Championships 2026 Interested party archive pending
- S3 750 million fans and 2.7 million data points: How IBM's AI powers Wimbledon from hidden 'Court 19' Established press archive pending
An error, newer info, a source?
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