AI Seen as Key to Turning Content Libraries into Shared Fan Experiences
At Variety's Entertainment & Technology Summit, executives discussed how AI can drive communal fan engagement beyond individual viewing. Panelists from EY, Warner Bros. Discovery, and Nvidia highlighted the potential of AI to unlock value in existing content libraries. They argued that companies possess valuable assets that AI can help activate for shared experiences.
The panel, titled "Beyond the Screen: How AI is the Catalyst for Next-Gen Experiences," convened at Variety's Entertainment & Technology Summit, an event presented by EY. Panelists included Vamsi Duvvuri, EY Americas' AI leader for technology, media, entertainment, and telecommunications; Simon Robinson, president of Global Experiences and Studio Operations at Warner Bros. Discovery; and Shari Reich, Nvidia's global head of audio and music developer relations. Their discussion centered on shifting AI's role from a purely individual viewing tool to a mechanism for collective, shared fan engagement.
The executives framed existing content libraries as underutilized assets, describing them as "crown jewels" that companies have yet to fully activate. The core argument was that AI can unlock value from these vast catalogs, transforming passive consumption into interactive communal experiences. This perspective positions AI not merely as a production or recommendation tool, but as a bridge connecting audiences to each other through the content they already love, potentially reshaping how studios monetize their back catalogs in an increasingly fragmented streaming landscape.
This shift could significantly alter how audiences engage with entertainment, moving from solitary streaming toward shared, interactive events that deepen fan communities. Studios and platforms may benefit from new revenue streams by activating dormant libraries, while fans gain richer, more participatory experiences. However, the reliance on AI for communal engagement could also raise questions about data privacy and the quality of algorithm-driven interactions, potentially reshaping social viewing habits in ways that are difficult to predict.