2026 ChinaJoy AI未来生态大会上，Funloom AI、阿里云、VAST、珀乐互动等企业代表围绕AI工作流从实验室到产线的规模化问题展开圆桌论坛[1]。与会代表指出，AI在游戏和内容产业落地过程中面临内容质量控制、推理成本高企、工程化实现困难等多重挑战[1]。
Funloom AI在本次大会展示了AI文游、RPG和互动影游三位一体的架构体系，已完成pre-A轮融资[1]。Funloom AI创始人吴同强调，AI内容创作的核心在于"心流构建"，用户应专注于创意层面，由AI来补齐专业知识[1]。
规模经济问题构成当前最突出的矛盾。与会企业代表指出，AI游戏面临"用户越多、成本越高"的规模不经济困境，纯API调用模式下毛利低于三成[1]。VAST强调，企业发展已经历能生成、能生产、能运行三个阶段，从Demo到真实生产管线的跨越是关键难点[1]。
在协作生态方面，珀乐互动透露与阿里云、开心麻花合作开发《羞羞的铁拳》项目，核心目标是实现数字资产在不同底模间的流转和定价[1]。与会者认为，未来12-18个月的关键变量包括生产关系改变、AI原生玩法诞生、推理成本下降、以及IP与模型深度绑定等方面[1]。
A roundtable forum at the 2026 ChinaJoy AI Future Ecology Conference brought together representatives from Funloom AI, Alibaba Cloud, VAST, and Poleplay Interactive to examine the critical obstacles facing artificial intelligence workflows as they transition from laboratory experimentation to production lines [1]. The discussion centered on core challenges encountered during AI implementation in gaming and content industries, including content quality control, escalating inference costs, and engineering implementation difficulties [1].
Industry participants identified several fundamental pain points in scaling AI operations. One representative emphasized that the primary challenge in AI gaming lies in an inverse economy of scale—as user numbers grow, operational costs rise correspondingly, with pure API-based models generating profit margins below 30 percent [1]. Another panelist outlined a developmental progression consisting of three critical stages: the ability to generate content, the capacity to produce at scale, and the capability to execute in real production pipelines, underscoring the significant gap between demonstration projects and actual production systems [1].
Funloom AI presented an integrated architecture spanning AI-generated literature games, RPGs, and interactive films, having completed a pre-A round of financing [1]. Poleplay Interactive disclosed an ongoing collaboration with Alibaba Cloud and Open Mahua on a digital content project, targeting the ability to facilitate digital asset circulation and pricing across different foundational models [1].
Looking forward, industry participants identified key variables for the next 12 to 18 months, including shifts in production relationships, the emergence of AI-native gameplay mechanics, reductions in inference costs, and deeper integration between intellectual properties and AI models [1].
