China’s AI music tools reshape songwriting and discovery

This article offers a ground‑level snapshot of how generative AI is being embedded into a major cultural industry in China, from AI‑assisted songwriting in Hangzhou’s digital music base to large‑scale deployment of Tencent Music’s “AI songwriting” features. The workflows described—prompting DeepSeek to draft lyrics, piping them into Suno V4 for full tracks, and using LLM‑powered recommenders that respond to fuzzy, emotional queries—illustrate how quickly human‑in‑the‑loop creativity is giving way to AI‑augmented production lines.([paper.people.com.cn](https://paper.people.com.cn/rmrbhwb/pc/content/202512/19/content_30125699.html))

Strategically, the scale numbers matter: tens of millions of AI‑generated songs and billions of plays signal that generative models are not a novelty layer but increasingly the default substrate for content creation and discovery in China’s music ecosystem. That creates vast behavioral datasets about how people interact with AI‑generated media, which can be fed back into models for preference learning, multimodal understanding, and agent design. It also normalizes AI as a co‑author in mainstream culture, which may reduce social resistance to more autonomous AI agents in other domains.

While this doesn’t push directly on AGI research, it accelerates the co‑evolution of humans and generative systems. As more of the cultural internet is generated by models and curated by AI assistants, future training data will increasingly be “model‑on‑model,” with all the feedback‑loop risks that implies. At the same time, the infrastructure, tooling, and product patterns refined in music recommendation will likely migrate to other experiential domains—games, education, virtual worlds—where richer, more agentic AI behaviors are being explored.