How AI Powers Chinese Microseries

The global entertainment landscape is undergoing a radical transformation, driven by the convergence of artificial intelligence (AI) and innovative content formats. In this context, AI marketing is emerging as a strategic process through which companies use AI solutions to personalize content, increase customer engagement, and gain actionable insights, ultimately generating positive business results.¹Within the entertainment industry, this application translates into a detailed understanding of viewer preferences, enabling content curation that aligns with individual tastes, improving the overall user experience and encouraging greater engagement.²AI is fundamentally redefining how content is created, personalized, and experienced—from automating creative processes to improving audience engagement.³

Meanwhile, Chinese microseries have emerged as an explosively growing entertainment phenomenon. Characterized by their concise and addictive format, with episodes lasting between one and two minutes, these series typically extend over around 100 episodes, optimized for viewing on smartphones and capturing attention in short bursts.⁴Since late 2022, these productions, rich in Chinese aesthetics and mythical references, have captivated vast audiences both in their home countries and internationally, prompting producers to aggressively expand into foreign markets.⁵

The purpose of this report is to take an in-depth look at how artificial intelligence has become a fundamental driver for the production, distribution, and, crucially, marketing of Chinese microseries. The synergy between AI and this entertainment format will be explored, detailing its specific applications, the tangible benefits it brings, the inherent challenges that must be addressed, and the future prospects of this powerful combination to maximize its global reach and profitability.

Microseries’ ability to capture attention in very short time segments aligns uniquely with the inherent strengths of AI-driven marketing. The “pocket-sized” format of microseries directly benefits from AI’s ability to rapidly analyze user data, identify preferences, and deliver highly relevant content and ads in real time. This relationship is almost symbiotic, where AI can learn from micro-interactions, such as viewing a one-minute clip, and tailor content recommendations or marketing messages for immediate and sustained engagement. This intrinsic fit of the microseries format with AI’s ability to manage fragmented attention is a key catalyst for its success and exponential growth.

II. The Chinese Microseries Phenomenon: An Exploding Market

Chinese microseries have cemented their position as a dominant player in global digital entertainment, thanks to a set of distinctive features and a bold expansion strategy.

Distinctive Features: Format, Content, Production

The format of these productions is an innovative fusion of the narrative of a soap opera and the immediacy of a TikTok reel.⁴Each episode, just one or two minutes long, is designed to be consumed on phone screens, adapting to the shorter attention spans of mobile audiences.⁴A typical series can run to around 100 episodes, allowing for quick and immersive viewing.

As for content, although the stories are low-budget and simplified, they focus on intense and addictive plots. Recurring themes include betrayal, revenge, family drama, and romance, with constant plot twists and turns.cliffhangersthat keep viewers hooked.⁴While many of these series are rooted in Chinese aesthetics and mythical references, for their global expansion they actively adapt to local cultures, incorporating habits, slang, and scenarios specific to international markets.⁵For example, Western markets combine the “billionaire boss” archetype with fantasy elements like vampires and werewolves, while Southeast Asian audiences prefer a mix of romance, family rivalries, and come-from-behind stories.⁷

Microseries production is characterized by an accelerated production cycle, which has allowed directors like Ju Guo to complete more than 30 series in just two years.⁵The efficiency and high production quality are remarkable, quickly capturing the attention of mobile audiences.⁶Unlike traditional television dramas, these productions typically employ low-budget sets, simple costumes, and a cast of mostly unknown actors, which contributes to their profitability.⁴

Global Market Growth and Expansion

The global microdrama market is experiencing a phase of explosive growth. Download numbers are expected to skyrocket from millions to tens of millions between 2023 and 2024, and the monthly user base will surpass 20 million in 2024.⁷In China, the online microdrama market is expected to reach 37.39 billion yuan in 2023, representing an impressive year-on-year growth of 267.65%.⁴Projections indicate that this market could expand to 100 billion yuan by 2027.⁴

Global expansion is a key pillar of this growth. More than 40 Chinese microseries apps have entered international markets, accumulating nearly 55 million downloads and generating $170 million in in-app purchases.⁴The global market is structured into three tiers: the mature North American market, led by the United States (which contributes more than 50% of in-app revenue); emerging markets such as Southeast Asia, Japan, and Korea; and high-potential regions such as Latin America and the Middle East.⁷It is notable that the Asia-Pacific region excels in microdrama app downloads and user engagement time.⁷

The following table illustrates the rapid growth and projection of the global Chinese microseries market:

Monetization and Success Models in Key Markets

The success of microseries depends largely on investments in traffic.streamingand advertising.⁴Advertising is a key component to attracting a highly profitable user base.⁴Although the cost of producing a program is relatively low, approximately $150,000 for a

remakeIn the US, millions are spent promoting these programs to potential viewers.⁴

The United States stands out as the largest consumer of microseries apps abroad, contributing between 60% and 70% of total revenue from these apps outside of China.⁴American viewers have also shown a remarkable willingness to pay for content.⁶Leading platforms like ReelShort employ a microtransaction-based monetization model and a virtual currency system, where users can purchase coins or watch ads to unlock episodes.⁸This model has been extraordinarily successful, with ReelShort surpassing Netflix in the US App Store entertainment rankings in November 2023.⁹

The strategy of these microseries is based on a globalized “quick hook.” Their content design, centered on drama andcliffhangersIn very short episodes, it is intrinsically designed to capture and retain attention instantly.⁴This quick engagement is a universal appeal that transcends cultural barriers, making the core content easily transferable globally. The brevity of the format ensures immediate gratification and a high re-engagement rate, crucial elements for mobile consumption. By combining this universal appeal with AI-powered localization, which includes voice synthesis, localization, and facial replacement technology for regionalization, cultural resonance is enhanced and production costs are substantially reduced.²This strategy enables a “globalization” perceived as “hyperlocalization,” facilitating rapid market penetration and a deep audience connection that traditional, more costly content models struggle to achieve. AI is used to scale cultural relevance without sacrificing efficiency.

There’s a seeming paradox between low production budgets and high marketing investment. Microseries are produced with modest budgets, simplified sets, and unknown actors.⁴However, millions are invested in its promotion, and advertising is essential to its success.⁴This contradiction reveals a deliberate strategic shift in the entertainment industry’s investment model. Success is not primarily based on lavish production values, but on efficient, high-volume content creation, enabled by the low-budget, fast-cycle format, combined with aggressive, data-driven marketing. The low cost of production allows for a disproportionately greater allocation of capital toward user acquisition, retention, and monetization. This suggests that content acts as a high-volume, low-cost “commodity,” designed for rapid and scalable monetization through optimized marketing and advertising. High return on ad spend (ROAS) figures validate this model, indicating that value is generated more by the efficient capture and monetization of audience attention than by the intrinsic cost of content production.

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III. Fundamentals of Marketing with Artificial Intelligence

Artificial intelligence has reshaped the digital marketing landscape, offering unprecedented capabilities for customer insight, personalization, and campaign optimization.

Key Concepts and Benefits of AI in Marketing

AI marketing is defined as the process by which companies leverage artificial intelligence solutions to personalize content, increase customer engagement, and gain actionable insights, with the ultimate goal of generating positive business results.¹Its benefits are multifaceted and transformative:

• Obtaining information from customer data:AI enables the exploitation of large volumes of customer data, including demographic information (name, gender, location), interaction information (service usage, social media following), behavioral information (purchase history, subscriptions), and attitudinal information (surveys, reviews).¹This capability is vital to understanding the target audience and their journey, facilitating accurate customer segmentation into groups based on shared characteristics or preferences.¹
• Improving customer experience with personalized content:By analyzing data and extracting insights, marketing teams can deliver personalized messages, such as targeted ads, personalized emails, and interactive quizzes.¹This personalization leads to greater customer satisfaction and loyalty, increased marketing return on investment (ROI), and cost savings through better-focused marketing strategies.¹
• Minimizing errors and improving data management:AI-driven automation dramatically reduces human error and optimizes the management of vast volumes of data, resulting in greater operational efficiency in the workflow.¹
• Increased marketing ROI:By targeting messages and campaigns more precisely and efficiently, AI increases marketing ROI, ensuring resources are allocated to audiences most likely to convert.¹

Current and Future Trends in AI in Digital Marketing (2024-2025)

The year 2024 marked a milestone in the widespread adoption of AI by marketers, with its integration into nearly every aspect of campaign creation and optimization.¹³Key trends for 2025 include:

• Hyper-personalization at scale:AI models continue to become more powerful, processing vast amounts of consumer behavior data to enable real-time adjustments to customer experiences.¹²This extends from content recommendations on platforms
  streamingto dynamic ads and personalized website experiences.
• AI-powered content creation:Generative AI is maturing, expanding beyond text to efficiently create videos, music, 3D visuals, and interactive content, significantly reducing production time and difficulty.¹³Tools like ChatGPT, Jasper, Canva AI, and Runway ML are examples of this evolution, allowing marketers to generate materials and launch campaigns with unprecedented speed.
• Predictive analytics as a non-negotiable element:AI and machine learning analyze historical data to predict future outcomes, anticipate customer behavior, and optimize marketing budget allocation.¹³This ability is essential for predicting market trends, minimizing risks, and maximizing ROI.
• AI-optimized advertising campaigns:AI has been integrated into nearly every aspect of pay-per-click (PPC) campaign management, from bidding and conversion optimization to campaign creation and launch. Campaign types like Performance Max and Advantage+ on platforms like Google Ads and Meta Ads simplify setup and enable continuous optimization.¹³
• Cookie-free, AI-powered audience segmentation:With the phasing out of third-party cookies and tightening privacy regulations, marketers are turning to first-party data and AI-powered segmentation to effectively reach target audiences.¹⁰AI analyzes behavioral patterns and interaction trends without relying on cookies, combining first-party data with other sources to create dynamic audience segments.
• Other trends:Voice search and conversational AI, AI-powered visual search (allowing consumers to find products using photos), and the use of AI to identifyinfluencerswith maximum ROI and predicting campaign results are also on the rise.¹³

AI is not simply a set of individual tools, but an “efficiency orchestrator” in modern marketing. While individual benefits such as error minimization and increased ROI are significant¹AI is transforming the entire marketing and content creation value chain. It automates repetitive tasks, streamlines complex data analysis, and improves campaign performance from start to finish.²This allows marketers to focus their time on high-level strategic planning, creative direction, and ethical oversight, rather than manual execution. This systemic efficiency is particularly critical for high-volume, fast-paced industries like microseries, allowing them to scale operations and respond to market demands with unprecedented agility.

IV. AI as a Strategic Driver in Microseries Marketing

The application of artificial intelligence in the field of Chinese microseries has transcended mere automation, becoming a strategic driver driving the personalization, optimization, and global expansion of this entertainment format.

Personalization and Audience Segmentation

AI is essential for understanding viewer preferences and behaviors at a granular level. Through deep learning capabilities, AI analyzes viewing history, search queries, and even time spent on specific titles.²This analysis allows platforms to suggest shows, movies, or episodes that align with a user’s individual interests and mood, significantly improving the overall experience.²

For microseries, this translates into much more precise audience segmentation, crucial for targeted ads and tailored content. AI segments audiences based on demographic, geographic, psychographic, and behavioral criteria.¹⁰AI tools process vast volumes of data to define ideal customer profiles, allowing offers and ads to be targeted to the right people at the right time, minimizing wasted resources.¹⁷This approach is particularly valuable for microseries that seek niche audiences, such as ReelShort’s success in specifically targeting middle-aged women interested in romantic dramas.⁸

Optimization of Advertising Campaigns

AI-powered advertising campaigns have become the norm, with platforms like Meta and Google integrating AI into pay-per-click (PPC) campaign management, from bidding and conversion optimization to campaign creation and launch.¹³A striking example of this effectiveness is the Mobupps case study with a Chinese microseries app, which achieved a Day 0 Return on Ad Spend (ROAS) of 144%, significantly exceeding the client’s target of 85%.⁴

Mobupps’ strategy included optimizing mobile traffic channels to attract a highly engaged audience and introducing Connected TV (CTV) traffic.⁴This dual approach allowed them to diversify user acquisition and reach a broader audience segment that consumes content on large screens but still interacts with mobile devices for apps and purchases. The result was a volume of 1,200 installs per day, demonstrating the effectiveness of a multifaceted AI-powered marketing strategy.⁴

AI-Powered Content Creation and Adaptation

AI is revolutionizing content creation for microseries. It can automate the generation of lyrics, audio, and scripts, streamlining the creative process.³AI-powered voice synthesis technology produces natural-sounding dubs in multiple languages, capturing the subtleties of the original performance while maintaining emotional impact across cultures.²In addition, AI is transforming the creation of visual effects (CGI/VFX), speeding up processes and enabling smaller studios to generate high-quality effects that previously required large budgets.²

Beyond creation, AI facilitates cultural localization and reduces production costs. It allows for adapting existing stories and incorporating local cultural elements.⁶Crucially, AI-powered facial replacement technology can regionalize characters, improving cultural resonance and substantially reducing production costs.⁷This capability is vital to the rapid and cost-effective global expansion of Chinese microseries, allowing content to resonate deeply with diverse audiences without incurring the costs associated with traditional multi-market production.

Predictive Analysis and Performance

AI provides crucial predictive analytics for content success and the optimization of release strategies. By examining large data sets, including social media sentiment, trailer views, and the historical performance of similar genres or actors, AI can predict a piece of content’s potential for success.²This allows for a more strategic allocation of marketing resources and can influence decisions about release dates to maximize audience reach and revenue.²

In addition, AI is capable of performing sentiment analysis andengagementof the audience. Process massive volumes of social media data, reviews, and viewing patterns to assess fan sentiment on projects, performance metrics, andengagement(such as when viewers drop out or get involved in thebinge-watching) and guide marketing and production strategies.¹²

AI acts as a facilitator of “hyper-localized globalization” for microseries. These productions aggressively seek foreign markets.⁵and demonstrate a clear intention to adapt to the “varied tastes of the market”⁷, even incorporating “local cultural elements” such as habits and slang.⁶AI offers advanced content adaptation capabilities, such as voice synthesis and localization.²and, even more strikingly, AI-powered facial replacement technology for regionalization.⁷This goes beyond simple translation, enabling visual and auditory cultural integration. Combined with hyper-personalization at scale¹³and precise audience segmentation¹⁰In marketing, microseries can achieve a unique form of “hyper-localized globalization.” They can produce content that feels authentically local and deeply resonates with diverse audiences around the world, while leveraging the inherent efficiency and scalability of AI-powered production and marketing. This provides a significant competitive advantage, enabling rapid market penetration and fostering deeper audience connections that traditional, less adaptable content models struggle to achieve.

AI creates a virtuous cycle in the microseries value chain. AI-powered production tools enable the rapid and cost-effective creation of high-volume, culturally adaptable content.²This content is efficiently marketed and distributed globally using AI for hyper-targeted advertising and audience acquisition, maximizing reach and monetization.⁴Crucially, the consumer data generated by this interaction is fed back into AI systems, informing future content creation (e.g., identifying popular plots, character archetypes, or cultural elements that resonate) and further refining marketing strategies for greater precision. This continuous, AI-powered feedback loop enables unprecedented agility and responsiveness to market demand, maximizing profitability and audience retention in a highly competitive landscape.

The following table summarizes the key applications of AI in microseries marketing:

V. Case Studies and Success Stories

The global success of Chinese microseries is not a coincidence, but the result of meticulously designed marketing and monetization strategies, increasingly powered by artificial intelligence.

Analysis of Marketing Strategies of Leading Platforms

ReelShort, launched in August 2022 by Crazy Maplet Studio, has established itself as a dominant player in the global microdrama app market, capturing 52% of downloads and 48% of revenue.⁷Its success is attributed to its studio’s prior experience in global web literature, a rigorous focus on script quality, and an aggressive advertising strategy.⁷ReelShort uses a combination of paid advertising on social media platforms like Meta (including Facebook and Instagram), social media marketing, and

influencersand strategic placement of digital content.⁸The platform attracts users by sharing dramatic clips and

cliffhangersthat generate intrigue.⁸Its monetization model, based on a virtual currency system where users can buy coins or watch ads to unlock episodes, encourages a strong

engagementand effective monetization.⁸In November 2023, ReelShort even surpassed Netflix in the US App Store entertainment rankings, briefly reaching number one.⁹

DramaBox, developed by Dian Zhong Tech and launched overseas in April 2023, has quickly achieved the revenue threshold of millions of dollars.⁷Its strategy focuses on translated Chinese microdramas, with notable success among the male demographic, where its share of male users soared to 43.5%.⁷

ShortMax, introduced by Jiuzhou Culture in September 2023, also shows an impressive track record in the market.⁷In addition to these platforms, AI tools such as

ShortX.aidemonstrate how automation drives the creation of short videos optimized for platforms like YouTube Shorts, Instagram Reels, TikTok, and Snapchat.²⁰These tools enable AI-powered image styles, music, subtitles, and voiceovers, making it easier to produce promotional content at scale.²⁰

Concrete Results and Lessons Learned

ReelShort’s success is undeniable, with series like “Fated to My Forbidden Alpha” and “The Double Life of My Billionaire Husband” garnering 110 million and 270 million views respectively in less than six months.⁷This underscores the enormous monetization potential and global reach of the microseries format.

The case study ofMobupps ⁴serves as a clear and quantifiable example of how targeted traffic strategies and AI-driven optimization can generate exceptional ROI. The client, a Chinese advertising app

streamingshort-form video, was looking to achieve an 85% ROAS on Day 0. However, Mobupps consistently exceeded this goal, achieving an impressive 144% ROAS on Day 0.⁴This was achieved by optimizing mobile traffic channels to attract a highly engaged audience and strategically introducing Connected TV (CTV) traffic to diversify user acquisition and reach a broader segment.⁴This combination resulted in a volume of 1,200 installs per day, demonstrating the importance of significant and strategically targeted advertising investment.⁴

The intrinsic ability of microseries to capture the attention of mobile audiences in just one or two minutes⁶and the high willingness to pay in key markets such as the US.⁶are critical factors that drive the success and profitability of this business model.

The success of microseries isn’t a coincidence; it’s an AI-powered “virality formula.” The microseries’ design, optimized for phone screens and short attention spans, is based oncliffhangersand an intense drama⁴, making them inherently addictive and prone to rapid consumption. Platforms like ReelShort actively use paid social media advertising and marketing.

influencers, sharing short dramatic clips to attract users.⁸AI, for its part, optimizes the distribution of this highly engaging content by identifying the most receptive audiences, predicting successful campaign outcomes, and, crucially, generating new promotional content optimized for short formats, such as trailers and summaries, tailored to specific platforms.¹³This process creates a feedback loop in which AI-driven promotion amplifies the viral potential of the microseries format, leading to rapid user acquisition, high

engagementand ultimately substantial income.

The following table summarizes monetization strategies and ROAS results for microseries, with Mobupps as a prime example:

VI. Challenges and Ethical Considerations in AI Adoption

Despite the immense potential of artificial intelligence in microseries marketing, its adoption comes with significant challenges and ethical considerations that must be proactively addressed to ensure sustainable and responsible development.

Privacy and User Data Protection

AI processes massive amounts of user data, including demographic, interaction, behavioral, and attitudinal information, to personalize and segment content.¹This capability, while powerful, poses an inherent risk: the possibility of disclosing a user’s identification without their consent, which represents a critical ethical issue.²¹

In an environment where privacy regulations like GDPR and CCPA are tightening and third-party cookies are being phased out, companies must implement strict first-party data protection measures.¹³It is essential to ensure complete transparency in the handling of user information and always obtain their explicit consent.²¹Minimizing the amount of data collected and anonymizing user identities are crucial practices for leveraging AI ethically and protecting individual privacy.²¹

Algorithmic Biases and the Need for Transparency

AI algorithms, when trained on historical data, can reflect and amplify biases existing in those data sets.²¹This can lead to discriminatory decisions or the exclusion of certain user groups. For example, an algorithm trained on biased data could prioritize male audiences in financial campaigns, automatically ignoring women with similar profiles, which is not only unfair but also damaging to the brand’s image.²¹

The lack of transparency in AI decisions—that is, the difficulty in understanding the “why” behind recommendations or segmentations—complicates assessing their impartiality and can generate distrust among users and regulators.²¹It is essential to ensure that algorithms are clear, explainable, and trained with diverse and unbiased data sets.²¹Implementing regular algorithm audits is a critical measure to identify and correct any biases, ensuring a more ethical use of artificial intelligence.²¹

Reliability and Adaptability of AI in a Changing Environment

The reliability of AI systems can be questioned, especially if they rely on fragmentary or incomplete data. An example of this is seen in the context of Chinese courts, where the uneven digitization of information and the removal of cases from databases can affect the impartiality of AI decisions.²⁵For marketing, this translates into the need to ensure the quality and completeness of the data used to train AI models.

Furthermore, the rapid evolution of AI technology poses the challenge of ensuring that systems continually adapt to new scenarios and challenges.²²This requires continuous learning and constant adaptation to keep AI relevant and effective in a constantly changing environment.

A growing risk is disinformation, facilitated by AI throughdeepfakesand the creation of fake content that is difficult to distinguish from the real thing.²⁴This requires the development and adoption of verification tools and systems to counter its spread, especially in content promotion, where authenticity is key to audience trust.

The efficiency of AI, its main strength in marketing, is also its “double-edged sword.” AI’s ability to process vast volumes of data and make autonomous decisions for efficient communication and personalization²¹It is the driving force behind its adoption. However, this same efficiency is intrinsically linked to its most significant ethical challenges: algorithmic bias, privacy and data protection concerns, algorithm reliability, and a lack of transparency.²¹The ability to hyper-personalize content and ads relies on extensive data collection, which directly raises privacy concerns. Automating decision-making, while efficient, can inadvertently embed and scale biases present in training data, leading to discriminatory results. Furthermore, the ease of AI-powered content generation, such as

deepfakes, it also facilitates the spread of misinformation. This reveals a fundamental tension: maximizing the transformative potential of AI in marketing requires a vigilant and proactive approach to navigate its inherent ethical pitfalls. For Chinese microseries, this is amplified by the volume of content and user data involved, and the broader geopolitical context of AI development and data governance.

VII. Future and Strategic Recommendations

The future of Chinese microseries and their marketing will be deeply intertwined with the evolution and responsible adoption of artificial intelligence. Emerging trends suggest an even deeper and more sophisticated integration of AI throughout the entire value chain of this entertainment format.

Emerging Trends at the Intersection of AI and Microseries

• Maturing Generative AI:AI’s ability to create videos, music, and 3D visuals in ways that are more sophisticated and often indistinguishable from human production¹³This will enable greater automation in the production of microseries. This will range from script generation and music composition to complex visual effects and dynamic editing, shortening production cycles and enabling unprecedented creative experimentation.
• Extreme customization (“one person, one plot”):Kunlun Tech’s vision with “SkyReels” to realize the idea of “one person, one story”⁷points to a future where microseries will be even more personalized and tailored to individual niches. This will entail an evolution from a mass market to highly personalized and segmented viewer experiences, leading to greater market fragmentation and exploration.
• Deep integration across the entire value chain:AI will be further integrated into all stages of the microseries lifecycle. From conception and pre-production (script analysis, success prediction, AI-assisted casting decisions)¹⁴) to post-production (dynamic editing, CGI/VFX²) and distribution (ad inventory optimization, automated categorization¹²), AI will be an ever-present component.
• Low-cost, open-source AI models:China’s strategy of offering high-performance AI models at considerably lower prices, such as DeepSeek (which is 17 times cheaper than US alternatives) and Alibaba’s Qwen models²⁶, will democratize access to advanced tools for a broader range of microseries producers. This will further foster innovation and competition in the global market, allowing small studios to compete on quality and efficiency.

Implications for Producers, Distributors and Advertisers

• For producers:They will need to proactively adopt AI tools to maintain efficiency and competitiveness in high-volume, low-cost content creation. The focus will shift toward creative conceptualization, narrative quality, and identifying dramatic “hooks” that AI can amplify and replicate. It will be essential to explore content-level personalization for niche audiences, using AI to understand and meet very specific demands.
• For distributors (platforms):It will require continuous and strategic investment in AI for personalized recommendations, ultra-precise audience segmentation, and optimization of user acquisition campaigns. They will need to develop flexible monetization models, such as virtual currencies, subscriptions, and in-video advertising, that integrate seamlessly with AI-driven marketing strategies to maximize user value and retention.
• For advertisers:Unprecedented opportunities for ultra-precise audience targeting and highly efficient advertising campaigns will arise within the microseries ecosystem. Understanding the advanced capabilities of AI will be critical to maximizing the Return on Ad Spend (ROAS) and effectiveness of your campaigns in this rapidly consumed format, leveraging AI’s ability to identify optimal engagement moments and the most receptive user profiles.

Recommendations for Harnessing the Potential of AI Ethically and Effectively

To capitalize on the potential of AI in the microseries sector in a sustainable and responsible manner, the following strategic actions are recommended:

• Investment in AI governance:It is crucial to establish robust frameworks and processes to oversee the quality, reliability, and ethics of AI outputs. This includes implementing regular human reviews of all AI-generated content or decisions before public deployment.²⁸Human oversight is essential to mitigate risks and ensure consistency with brand values.
• Prioritize data privacy and security:With the elimination of third-party cookies and the rise of privacy regulations, robust first-party data protection measures must be implemented. It is imperative to ensure complete transparency in the use of user information, always obtaining their explicit consent, and adopting data minimization and anonymization practices.¹³
• Mitigate algorithmic biases and promote transparency:It is essential to train AI algorithms with diverse and unbiased data sets to avoid perpetuating bias. Regular audits of algorithms should be conducted to identify and correct any discrimination. Furthermore, transparency in AI decision-making must be a priority, allowing algorithmic decisions to be explainable and justifiable.²¹
• Promoting AI adaptability and reliability:Given the rapid technological evolution, companies must invest in AI systems that can continuously adapt to new scenarios and challenges. This requires a focus on continuous model learning and ongoing validation of their reliability, especially in the detection and prevention of AI-generated misinformation.²²
• Promoting human-AI collaboration:AI should be seen as a tool that enhances human capabilities, not replaces them. Fostering collaboration between creative and marketing teams with AI tools can generate superior results, combining machine efficiency with human intuition and creativity.

Conclusions

The intersection of artificial intelligence and Chinese microseries represents one of the most promising and transformative dynamics in the global entertainment industry. Microseries, with their short, addictive format, have demonstrated an exceptional ability to capture and retain attention in the era of “fragmented attention,” rapidly expanding into international markets and generating substantial revenue.

AI acts as an “efficiency orchestrator” and an enabler of “hyper-localized globalization.” It enables granular understanding of viewer preferences, mass personalization of content and advertising, and unprecedented optimization of marketing campaigns, as evidenced by impressive ROAS results. Furthermore, AI revolutionizes content creation and adaptation, from script generation and dubbing to cultural localization using advanced technologies. This AI-driven “virtuous cycle” in the microseries value chain enables fast and cost-effective production, efficient distribution, and continuous feedback that informs future creations, maximizing profitability andengagement.

However, this powerful synergy presents a double-edged sword. The efficiency and power of AI in marketing bring with it significant ethical challenges, particularly regarding user privacy and data protection, the risk of algorithmic bias, and the need for transparency and reliability. The rapid expansion of Chinese microseries, driven by low-cost AI models, amplifies these concerns, demanding rigorous governance and a commitment to ethical practices.

To fully realize the potential of AI, producers, distributors, and advertisers must invest in AI governance frameworks, prioritize data privacy and security, actively mitigate algorithmic biases, and foster effective human-AI collaboration. By doing so, the Chinese microseries industry can continue its explosive growth trajectory, delivering personalized and culturally resonant entertainment experiences to a global audience while responsibly navigating the complexities of the AI era.

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