AI仙界视频引围观 单条获赞超300万；胡楚靓AI工作台获110万点赞 | AIGC热门精选

This article is a curated collection of trending AIGC content from AI New Rank, compiling the most popular AI-generated content across the Chinese internet recently. It covers both viral trending highlights and hands-on actionable tips that average people can follow.

1. Trending recent AI content highlights: Creator Qiguang on Douyin went viral with his "Daily Life in Fairy Realm" AI video series. One video has garnered over 3.15 million likes: with no plot or dialogue, it accurately captures the public's imagination of the Chinese xianxia (immortal) fantasy world, and many viewers repeatedly watch it as a digital wallpaper. Other viral hits include the multi-style AI short drama *The Witch Cannot Fall In Love*, a Shaw Brothers-style anti-fraud short film "Fake Horse Scam" starring a cat, and an AI-generated disaster video set in Miami, all of which have accumulated hundreds of millions or tens of millions of views with highly creative concepts.

2. Hands-on AI projects for regular users: Influencer Hu Chuliang has popularized the trend of building a custom personal workspace with AI. Users only need to describe their needs in natural language, and AI can generate a personal webpage with features for habit tracking, content ideation, and work review. Currently, step-by-step tutorials for this project are sold for just 1 to 2 USD on secondhand platforms and social media, so anyone can learn to build one themselves.

This article summarizes recent viral AIGC content trends and user preferences, offering insights to help brands shape their content marketing strategies and align with evolving consumer demand.

1. Current user content preferences: Users respond best to content that aligns with their cultural imagination and combines creativity with unexpected contrast. For example, xianxia fairy content resonates deeply with the romantic fantasy of Chinese audiences, while AI short dramas blending K-drama aesthetics, U.S. drama style, and Taiwanese drama dialogue have also won broad user acceptance. Content that combines original creativity with unexpected contrast is far more likely to go viral.

2. Takeaways for brand content marketing: AI enables low-cost, consistent production of serialized content. In the case profiled, a creator was able to release new xianxia content daily while delivering strong engagement for every post. Brands can similarly leverage AI to build their own owned content IP and lower the barrier to content production. Additionally, AI content can already effectively deliver science communication and public education, as seen in viral anti-fraud and firefighting safety campaigns. Brands can combine public welfare科普 with AI content to expand their reach and boost brand reputation.

3. Key risk to note: Unlabeled AI-generated content easily sparks controversy over authenticity and damages brand credibility. Brands should clearly label any AI-generated content they publish.

This article outlines new opportunities and potential risks in the AIGC content space, providing actionable insights for sellers looking to monetize AI content.

1. Traffic growth opportunities: AIGC content still offers massive traffic红利, with viral hits emerging across multiple niche segments: creative Chinese-style content, cross-genre fusion short dramas, creative科普, and AI tool tutorials all generate high engagement. A 33-second plot-free xianxia video can earn 3.15 million likes, for example, with a far lower traffic acquisition cost than traditional content.

2. New monetization opportunities: AI trends have already spawned mature low-ticket monetization paths. Following Hu Chuliang's popularization of AI custom workspaces, related tutorials sell for 1 to 2 USD, with some single links selling more than 100 units. Small sellers can enter this niche segment of AI tutorial education, which offers low barriers to entry and fast monetization.

3. Risk warning: Unlabeled AI-generated content easily triggers public skepticism and compliance issues. Sellers should proactively and clearly label all AI content they publish to avoid unnecessary controversy.

This article outlines current end-user aesthetic preferences and real-world AI industry adoption, offering insights for factories pursuing digital transformation and e-commerce expansion.

1. Guidance for product design and development: End users favor content and products that align with local cultural aesthetics and combine creative contrast. Chinese consumers have a natural emotional connection to xianxia themes, which has led to millions of likes for AI-generated xianxia content, while anti-fraud shorts blending ancient themes with modern creativity have also found massive audiences. For factories producing cultural and creative products or branded merchandise, developing products aligned with this user aesthetic will greatly increase the chance of market acceptance.

2. New commercial opportunities for e-commerce operations: AI enables extremely low-cost, consistent high-frequency production of serialized content. When factories build their own direct-to-consumer e-commerce channels and rely on content to drive traffic, they can use AI tools to quickly produce引流 content, cut content production costs, and maintain consistent posting and account engagement.

3. Lessons for digital transformation: AI has already been adopted for content production and personal tool building by everyday users. Factories undergoing digital transformation can test integrating AI tools to cut operational and marketing costs and improve overall operational efficiency.

This article outlines current AIGC industry trends and unmet pain points, providing insights for AIGC-related service providers.

1. Industry development trends: AIGC has moved beyond pure technology demonstration and entered an era of mass accessible practical creation. Amateur creators, influencers, and even official institutions are now widely using AI to produce content across multiple scenarios: short-form entertainment video, short and long-form drama, public科普, and personal tool building. Industry adoption is progressing far faster than initially expected.

2. Unmet user needs: Ordinary users still face notable barriers when building custom AI-powered tools. After Hu Chuliang popularized AI workspaces, massive demand for paid tutorials emerged, indicating users want more lightweight, user-friendly AI products. Service providers can build easier-to-use AI tools targeting mainstream end-users to capture mass market demand.

3. Existing industry challenges: The lack of mandatory AI content labeling has become a major source of controversy. Service providers can add automatic labeling features at the AI content output end to help creators publish content compliantly and solve this key industry pain point.

This article highlights gaps in current AI content management on content platforms and identifies new industry opportunities, offering guidance for platform operations and governance.

1. Existing risks and challenges: In one case covered in the article, an unlabeled AI-generated video of a disaster in Miami gained nearly 700 million views in two days, with captions misleading users into believing it was real footage. AI content routinely outperforms real user-generated content under algorithmic recommendation, which has sparked public questioning of platform algorithm priorities and exposed incomplete AI content labeling mechanisms on platforms.

2. Priorities for operational and governance improvement: Reliance on voluntary creator labeling is not sufficient to solve this problem. Platforms need to improve AI content detection mechanisms and add mandatory labeling requirements during the publishing process to uphold the public's right to information and avoid industry ethical risks.

3. New growth opportunities: AIGC content currently offers clear traffic红利, and AI creators across all categories are regularly producing viral hits. Platforms can launch dedicated recruitment and support programs for AI creators to attract more creators to the platform and drive overall content traffic growth.

This article presents the latest developments in the AIGC industry and newly emerging issues, providing first-hand insights for industry researchers.

1. New industry development trends: AIGC has now achieved mass market adoption. Amateurs and influencers alike can proficiently use AI tools to create content covering entertainment,科普, and personal tools, and mature monetization models have already emerged: for example, knowledge payment for AI tutorials has surpassed 100 units sold per single link. The era of mass adoption for lightweight AI applications has arrived.

2. Newly emerging industry issues: Under algorithmic recommendation systems, AI-generated content is far more likely to gain high traffic, but content labeling mechanisms for AI are seriously underdeveloped. Unlabeled AI content can easily mislead the public, and platform regulation lags far behind current development, sparking ethical debate over content authenticity and algorithmic priorities that merits in-depth research.

3. New research directions: Beyond content generation, AIGC now enables ordinary users to quickly build custom personal tools. Mass market applications of Vibe coding and AI Agents have already emerged, and new business models and market segments are taking shape, offering significant research value.