Agenda

This session demystifies how AI can reliably produce high‑fidelity art, animation and video assets for live game production. It begins with "brand‑trained" pipelines that ingest existing assets and learn a studio's visual language; these pipelines handle data curation, model training, evaluation, inference and operations. Examples include stylized avatar creation, novel character and IP generation and synthetic dataset production. The talk then explores a Swiss‑army‑knife toolkit: LLM‑driven tools, multi‑view 3D reconstruction, multi‑modal character generation using segment prompts and image‑likeness matching, and gameplay‑footage analysis that automatically selects segments, composes trailers and adds AI‑generated audio. It covers personalized video flows, metahuman localization and motion capture via text prompts. Throughout, the emphasis is on responsible adoption, knowledge‑sharing and staying ahead of rapid technological change.

Takeaway

Attendees will learn how to build production‑ready AI pipelines—combining open‑ and closed‑source models—to create on‑brand 2D/3D/video assets, synthesize data, automate asset creation and personalize content. They'll also understand governance and workflow integration, ensuring AI enhances rather than disrupts game development.

Intended Audience

This talk targets studio leaders, producers, art/technical directors, pipeline engineers and developers who want to integrate AI into active production. It assumes familiarity with modern game development pipelines but requires no machine‑learning expertise, focusing instead on practical workflows, cross‑disciplinary collaboration and management considerations.