FIAT/IFTA World Conference 2026

The Images Sport AI Project is the second major phase of the IOC’s long‑term digital transformation of its archival ecosystem, following the successful migration from bespoke on‑premises systems to a cloud‑based, integrated architecture between 2021 and 2024. This foundation introduced seven interoperable platforms for preservation, access and analytics, and enabled the structured migration of more than 85,000 audiovisual assets and 928,000 photographs with full metadata. 
Launched in 2024 in alignment with the IOC AI Agenda, the Images Sport AI Project introduces state‑of‑the‑art artificial intelligence into both front‑end discovery and back‑end documentation workflows. Its dual objective is to enhance search capabilities in The Olympic Media Library (TOML) and accelerate metadata creation within the Media Asset Management system through automated tagging. 
Front‑end innovations include AI‑driven image and video similarity search, enabling users to retrieve visually related content that traditional text‑based descriptions cannot capture. A conversational search prototype extends this further by combining TOML metadata, multimodal search and IOC data, allowing natural‑language queries and richer discovery pathways. 
On the back end, automated tagging uses deep‑learning models are developed to generate sport‑specific vocabularies (actions, equipment, venues), general actions, logos, symbols and framing descriptors, while deliberately excluding athletes’ identities or emotions to ensure compliance with legal and ethical frameworks. Winter sports vocabularies form the basis for pilot deployments ahead of Milano Cortina 2026, with Summer sports following  for Dakar 2026 Youth Olympic Games and Los Angeles 2028 Olympic Games. 
The project directly addresses key questions about large‑scale infrastructure, automation, authority control and ethical metadata governance. It positions the IOC Archives as a global laboratory for innovation within Sport Archives, demonstrating how AI can strengthen discoverability, operational efficiency and long‑term stewardship across extensive heritage collections.