--- title: "From \"Content Production\" to \"Worldview Accounting\": How Sustainable IP Is Built in the AI Era" author: "Unique Research" sourcePublication: "Unique Research Substack" originalPublishedAt: "2026-06-10T12:01:29+00:00" canonical: "https://ffcap.cn/en/research/src-20260610-01html" source: "https://uniqueresearch.substack.com/p/src-20260610-01html" language: "en" --- # From "Content Production" to "Worldview Accounting": How Sustainable IP Is Built in the AI Era _Original · Unique Research · 2026-06-10_ _Editor's note: The first-person report and its judgments belong to the original Chinese author. This English rendition retains the full FizzDragon interview with David Wang (Associate VP of Global Distribution), all seven themed sections, and the complete 15-question Q&A. All named companies, products, and people are preserved. Company, personal and product names are transliterated where official English forms remain unverified. Interviewee statements are source attributions, not independently verified findings._ AI Industry Observation What AI film and television is changing first is not the film industry, but who is qualified to tell stories. The lower the cost of technology, the more expensive human judgment becomes. " We are helping creators "rent out" their creativity to earn income — it's like a "Didi" for creativity. Many people's understanding of AI video is still stuck on a single frame: type a prompt, and a few shots are generated seconds later. This understanding isn't wrong, but it's far too narrow. If AI film and television merely makes video generation faster, it will eventually become just another content tool. Tools get cheaper, they homogenize, they get replaced by new models. The change worth watching is not in "generation" itself, but in what happens after generation: who can participate in creation, who can organize collaboration, who can turn a work into IP, who can carry a story across language, market, and cultural boundaries. When FizzDragon Associate VP of Global Distribution David Wang (王大卫) spoke with Unique Research, he used a very blunt metaphor to explain FizzDragon: "We are helping creators 'rent out' their creativity to earn income — it's like a 'Didi' for creativity." This statement pushes the essence of AI film and television one layer deeper. AI isn't simply making filmmaking cheaper. It is reconnecting people who could never enter the film industry into a global content production system. Teachers, designers, engineers, students — even people with no film training — as long as they have a story, a visual sense, and a desire to express, they may use AI to turn the world in their heads into works. In the past, the barriers to the film industry were built jointly by equipment, capital, teams, specialized division of labor, and distribution channels. Today, models are dismantling the first few barriers, but the last barrier has hardened: how does a work get seen, how does a story get remembered, how does IP keep growing. This is the dividing line where AI film and television truly enters the industrial stage. It isn't who generates faster, but who can organize more people to tell more vivid stories. The Biggest Barrier AI Lowers Is Not Technology, but "Can I Even Start" The most direct change in AI film and television is lowering the production barrier. David Wang believes that AI lowers the technical, capital, and team barriers all at once. In the past, if someone couldn't shoot, couldn't edit, had no crew and no budget, it was very hard to enter film production. Even with a complete story, it could only stay in text, sketches, or imagination. But he emphasizes another change even more: AI lowers the psychological barrier. This is often underestimated. Many people aren't without a desire to create; they simply don't dare start. They worry they aren't professional enough, have no resources, won't do it well, and don't know how to turn a story into images. Traditional film industry packaged "creation" into a highly specialized system, and ordinary people could hardly tell which part they could join. For the first time, AI lets ordinary people quickly see their own ideas visualized. This is instant feedback. A character, a line of dialogue, a scene, an atmosphere can be presented in a short time. Even if the result isn't perfect, it's enough to let a creator confirm one thing: this idea isn't empty; it can be pushed forward. David Wang mentioned that after many creators use FizzDragon, the biggest feedback isn't "efficiency improved" but "I finally started creating." This matters more than efficiency. Efficiency belongs to people already inside the system; starting belongs to people once locked outside. The first wave of AI film and television dividends isn't saving mature teams a few days, but letting a large number of formerly silent stories enter the production pipeline for the first time. So what AI unleashes first is not professional directors, nor professional producers, but "people who have stories and visual sense in their heads but once had no ability to complete production." They may never have entered the film industry, yet they possess powerful imaginations. AI gives these imaginations their first chance to be seen. This is also what makes AIGC film and television different from traditional video tools. It isn't making professional tools lighter; it's connecting non-professional people to professional expression. When the first step of creation is rewritten, the entrance to the industry is rewritten too. AI Film and Television Can't Be Just a Generation Tool, Because Filmmaking Has Never Been One Person's Job Generation tools solve the problem of "making a clip"; film platforms must solve the problem of "completing a project." These are not the same thing. FizzDragon hasn't positioned itself only as an AI video generation tool; it splits the platform into AI Studio, Crew Network, and IP Plaza. The logic behind it is clear: AI film and television is not a button, but a new set of production relations. David Wang says filmmaking has never been one person's job. Even if AI can complete more and more production stages, collaboration between creators won't decrease; instead it will matter more. The reason is that AI solves production efficiency, but what remains truly scarce is creativity, taste, judgment, and emotional expression. The lower the cost of technology, the more expensive human judgment becomes. This will change the definition of film and television roles. Future screenwriters won't only write dialogue and plot; they'll be more like worldview designers. Directors won't only run the set; they'll be more like creative directors. Visual artists won't only produce images; they'll become style architects. Voice actors won't only complete recording; they'll become character shapers. Editors won't only stitch materials; they'll become rhythm designers. AI will replace a great deal of repetitive labor, but it will amplify the importance of creative decisions. This is also why the "AIcrew" concept holds. A creator of the future may own their own virtual crew: AI director, AI cinematographer, AI composer, AI animator. At the same time, they still need to collaborate with real creators. Future film teams may become a hybrid structure of "1 creator + multiple AI Agents + a few human experts." This structure looks lighter, but demands more. In the past, a team's capability was determined by its roles. In the future, a team's capability will be determined by how it is organized. Whoever can combine AI Agents and human experts into an efficient crew can complete more complex content production at lower cost. Therefore, competition among AI film and television platforms won't stop at model capability. Models will upgrade, tools will spread, generation capabilities will converge. What's truly valuable is the network connecting talent, projects, capital, and audiences. David Wang's judgment is direct: "What will be most valuable in the future is not the tool, but the network that connects talent, projects, capital, and audiences." This sentence is the key to understanding FizzDragon. AI Studio provides creation tools; Crew Network connects creators; IP Plaza handles the trading, incubation, and co-creation that come after a work. What it tries to build is not a production button, but a path from story to work, from work to IP, from IP to global markets. In AI film and television, generation is only the starting point. Real industrial value happens after generation. Content Production Will Get Cheaper, But IP Won't Automatically Become Valuable AI makes content production faster, but what has always been hard in the content industry is never "production." What's hard is giving a work life. Short films can be generated quickly, characters designed quickly, scenes iterated quickly. But why does an audience remember you? Why does a story extend? Why can a character be consumed repeatedly? These questions won't solve themselves just because AI appears. David Wang believes that for AIGC film and television to move from one-off shorts to sustainable IP, the key is shifting from "content production" to "worldview production." A good IP is not one work, but a universe that keeps growing new stories. This points to a real contradiction in AI content: the easier production becomes, the easier a single piece of content loses scarcity. In the past, production cost itself was a filtering mechanism. That a project could be filmed proved it had at least crossed capital, team, and production barriers. After AI dismantles these barriers, content volume rises and attention becomes scarcer. At this point, the value of IP no longer comes from "I made a work," but from "can I continuously organize characters, worldview, fans, and business partnerships." The path FizzDragon gives from AIGC film and television to IP is: Story → Community → Worldview → Series Content → Brand Partnership → Global Distribution → Long-term IP Operation. This path shows that IP in the AI era is not a one-time generated result, but the product of continuous collaboration. In the past, IP development was linear: the creator finished the work, the film company developed it, channels distributed it, audiences consumed it. Layer upon layer of barriers sat in between. Now it is becoming networked: creators, fans, brands, investors may all participate in IP's growth. Many future IPs may no longer be created by one film company alone, but incubated jointly by a global community. This brings new problems: copyright, attribution, contribution, and IP ownership will become more complex. David Wang's view is that AI itself is not the creator; humans are. The future needs more transparent contribution-record mechanisms, and blockchain technology may be used to track who provided the story, who did the character design, who participated in production, and who contributed a critical stage. This is not a technical detail; it is the infrastructure for whether the AI content industry can scale. If contribution can't be confirmed, collaboration can't continue. If attribution isn't clear, IP can't be traded. If ownership can't be allocated, community co-creation stays a slogan. For AI film and television to enter the commercial stage, it can't only solve "how to generate"; it must also solve "how to keep accounts." The Quality Standard of AI Film and Television Ultimately Comes Back to Story The easiest place to misjudge AI video is mistaking technical effect for work quality. Whether the visuals are refined, the shots fluid, the style consistent — these matter, of course. But they are only the baseline. After AI-generated content appears in volume, visual spectacle will quickly depreciate, and audiences will tire faster. David Wang believes that in judging a future AIGC work, one shouldn't only look at technical effect, but at four things: whether there is emotional resonance, whether there is a unique point of view, whether there is cultural value, and whether it can be remembered by audiences. "What audiences ultimately remember is never the prompt, but the story." This is a reminder about the AI film and television bubble. When everyone can generate beautiful images, beautiful images no longer constitute a barrier. The real barrier returns to narrative, character, rhythm, cultural understanding, and emotional expression. This is also why AIGC film and television competitions matter within the ecosystem. They aren't just work showcases, nor just market education. David Wang believes competitions carry four functions at once: talent discovery, project incubation, market education, and industry connection. Many future creators, directors, and IP projects may first be discovered in competitions. Behind this is actually a new filtering mechanism. The traditional film industry used academies, studios, production companies, and festival circuits to discover talent. AI film and television needs new entrances. Competitions, communities, platform leaderboards, co-creation projects, distribution partnerships may all become discovery mechanisms for a new generation of creators. When the production barrier lowers, the filtering mechanism becomes more important. Who can discover good stories, identify good creators, push early works to larger markets — that person holds the key nodes in the AI film and television ecosystem. AI Puts Global Creators on the Same Starting Line, But Cross-cultural Communication Is Still Hard AI film and television naturally has a global attribute. The same tools can be used simultaneously by creators in Singapore, Mumbai, Jakarta, and Nairobi. In the past, content production capability was concentrated in a few markets, a few companies, and a few specialized talents. AI lays creation tools flat across more regions, letting global creators for the first time stand on a relatively close starting line. This will promote global cultural exchange and change the production map of film and television content. FizzDragon's current international collaboration focus revolves around AIGC film and television, education, and creator ecosystem building, connecting mainland China, Southeast Asia, Hong Kong, the Middle East, and European markets, and advancing creator communities, international competitions, education and training, and IP incubation partnerships. But going global isn't translating content into another language. David Wang's judgment on the challenge of AIGC film and television going overseas is clear: the biggest obstacle isn't language, but cultural understanding. "Translating a line of dialogue is easy, but understanding why another culture is moved by a certain story is hard." This is the reality every piece of AI content going overseas encounters. AI can lower language costs and production costs, but it can't automatically understand a market's humor, taboos, aesthetics, historical memory, family structures, and emotional triggers. Cross-cultural narrative ability will matter more than AI technical capability. Different regions also accept AIGC differently. David Wang observes that Asian creators care more about commercialization and efficiency, European creators more about artistic expression, North American creators more about IP and market scale, and Middle East markets more about national strategy and industrial upgrading. But all regions share one thing: they all want content production done at lower cost and higher efficiency. This means AI film and television globalization won't have a single path. In Asia, it may first enter short dramas, advertising, branded content, and commercial projects. In Europe, it may appear more as artistic experimentation and festival formats. In North America, it will revolve around IP development and market scale. In the Middle East, it may embed into national cultural industries and digital economy strategies. Even for the same AI film and television, different markets will grow different business models. A true global platform must understand these differences, rather than covering every market with one tool logic. What "Pirate Queen Zheng Yi Sao" Validates Is Not the Success of a Single Film, but a New Mode of Production For AIGC film and television to move into industry, it ultimately needs case validation. The long-form AIGC film Pirate Queen Zheng Yi Sao (《郑一嫂》) produced by FizzDragon is an important sample. This film was co-created by over 130 artists from 13 countries and regions, has already screened in cinemas in Singapore and Malaysia, and been exhibited at multiple international events. What's worth noting about this case isn't just that "AI helped complete a feature film." More crucially, it validates a cross-region, cross-specialty, cross-cultural collaborative production method. In the past, a feature film often relied on a highly centralized production system. The creative leads, team, budget, shooting, post-production, and distribution usually revolved around one central organization. But Zheng Yi Sao's production method is closer to distributed collaboration: artists from different countries and regions participate together, with AI becoming the infrastructure connecting creativity, production, and delivery. This aligns with David Wang's judgment on the AIGC film and television industry over the next three years. He believes the biggest change ahead isn't how long a single model can generate video, nor whether a single AI creator can commercialize, but that global collaborative production becomes the norm. A future film may be jointly completed by Singaporean planning, Chinese screenwriting, Indian animators, European composers, and an American distribution team, with AI becoming the infrastructure connecting these people. This isn't a simple replacement of the traditional film industry, but the addition of a new production paradigm. The traditional film industry will still exist; big productions, theatrical blockbusters, and professional crews won't disappear. But alongside it will emerge a lighter, more distributed, more global content production network. It won't necessarily start from Hollywood, nor necessarily be led by large studios, but may be jointly driven by platforms, communities, creators, and IP holders. The opportunity of AI film and television isn't using machines to replicate the old industry, but using new organization to produce stories that once could not be produced. AI Won't Replace Creators, but It Will Redistribute Creators' Opportunities The most common anxiety about AI film and television is: will AI replace creators? David Wang's answer is: FizzDragon doesn't believe AI will replace creators, but will unleash more creators. This judgment can't stay only at the values level; it must be viewed within industrial structure. AI will indeed replace some repetitive labor and compress the room for certain junior roles. Low-complexity image generation, material processing, simple editing, basic voiceover, storyboard sketches will all be quickly covered by tools. But at the same time, AI will also expand the total supply of creators. People who once had no chance to enter the film system will gain expressive ability through AI. People who once could only do a single role will expand into composite creators through AI. People once constrained by local markets will enter global collaboration through platforms and distribution networks. So AI's impact on creators isn't simple "replacement" or "protection," but a redistribution of opportunity. Some skills will depreciate, some judgments will appreciate. Repetitive execution will depreciate; creative organization will appreciate. Single-point ability will depreciate; cross-role collaboration ability will appreciate. Tool proficiency is just an entry ticket; the real barrier is taste, narrative, cultural understanding, and resource connection. What matters most in the future may not be AI itself, but how human creativity is reorganized and connected. This is also the industrial position FizzDragon tries to seize. It isn't only betting on AI-generated video, but on a larger shift: across the world there is a great deal of "idle creativity," AI will lower the threshold for this creativity to enter film production, and the platform is responsible for connecting these people, projects, IP, education, competitions, and distribution. When creativity starts being dispatched like transport capacity, the structure of the film industry will change. The Endgame of AI Film and Television Is Not That Everyone Can Generate Video, but That More People Can Complete Expression In the past, the core problem of the film industry was resources. Whoever had money, teams, and channels was closer to the audience. After AI, resources still matter, but the question is changing. Creators no longer only ask "can I shoot it," but "can I organize people"; works no longer only ask "can I generate it," but "can I be seen, remembered, and continuously developed"; platforms no longer only ask "can I provide tools," but "can I connect creators, IP, capital, and global markets." What truly changes the film industry isn't making video generation faster. It changes who is qualified to tell stories, how collaboration happens, and how content value is formed. David Wang said at the end of the interview: "What truly changes the film industry isn't making video generation faster, but giving more people around the world who once had no chance to tell stories the first chance to be heard by the world." This may be what's most worth watching about AI film and television. When more people who once had no chance to enter the film industry start telling stories, what the film industry faces is not just a technical upgrade, but an expansion of the creator population. The question also sharpens: When everyone can start creating, who can still make the world willing to keep listening? Interview Highlights Q&A Q1: Without the official introduction, how would you explain what FizzDragon does to a creator who knows nothing about it? David Wang: We are helping creators "rent out" their creativity to earn income, like a "Didi" for creativity. In the past, many people had ideas, stories, and taste, but no chance to enter the film industry. What FizzDragon wants to do is connect this creativity scattered around the world, let it participate in real content production, and ultimately get rewarded. Q2: Many people understand AI video as typing a prompt to generate a few shots. Why did FizzDragon choose to enter from AI film production and a storyteller platform? David Wang: Because we don't just want to make a video generation tool. Through AI, we want to let more people outside film specialization enter global filmmaking. In the past, if you couldn't shoot, couldn't edit, had no team, it was hard for one person to participate in filmmaking. But today, a teacher, designer, engineer, or student can all turn their own stories into works through AI. AI video is only the entrance; the real opportunity is letting more people become storytellers. Q3: How do you view the statement that "AI lowers the barrier to film creation"? David Wang: AI lowers the technical, capital, and team barriers at the same time, but most importantly, it lowers the psychological barrier. Many people have always had a desire to create; they just don't dare start. They feel they aren't professional enough, have no resources, and don't know if they can do it well. For the first time, AI lets ordinary people quickly see their ideas visualized, and this positive feedback unleashes many people's creative potential. After many creators use FizzDragon, the biggest feedback isn't "efficiency improved," but "I finally started creating." Q4: What kind of creator does AI unleash first? David Wang: AI first unleashes people who have stories and visual sense in their heads but once had no production ability. They may never have entered the film industry, nor had professional training, but they have strong imaginations. In the past these imaginations were hard to see; now AI gives them their first chance to be presented. StoryOS integrates AI director, AI screenwriter, AI storyboard, and AI art capabilities, helping creators generate images and video faster and move stories from ideas into the production pipeline. Q5: Why can't AI film and television be just a generation tool, but must build a creator ecosystem? David Wang: Because filmmaking has never been one person's job. AI can help one person complete many production stages, but truly valuable works often still require collaboration between creators. We hope creators can find each other through the platform, form small crews, and complete projects together. What will be most valuable in the future is not the tool, but the network that connects talent, projects, capital, and audiences. Q6: As AI can complete more and more production stages, will collaboration between human creators decrease? David Wang: No; it will instead become more important. AI solves production efficiency, but what's truly scarce is creativity, taste, judgment, and emotional expression. As the cost of technology approaches zero, the ability of people to collaborate with each other becomes the greatest competitive advantage. The future isn't human creators isolated by AI, but human creators needing to learn to work with AI and with other people. Q7: In the AI film and television era, what will happen to the roles of screenwriters, directors, visual artists, voice actors, and editors? David Wang: These roles won't simply disappear, but will be redefined. Future screenwriters will be more like worldview designers, directors more like creative directors, visual artists become style architects, voice actors become character shapers, and editors become rhythm designers. AI will replace a great deal of repetitive labor, but it will amplify the importance of creative decisions. What truly matters isn't whether you can operate tools, but whether you can make judgments. Q8: What do you think of the "AIcrew" concept? David Wang: A creator in the future may well own their own virtual crew. This virtual crew can include an AI director, AI cinematographer, AI composer, AI animator. At the same time, they will still collaborate with real human creators. Future film teams may be a hybrid structure of "1 creator + multiple AI Agents + a few human experts." AI will make teams lighter, but it won't make collaboration unimportant. Q9: If global creators can all use similar AI tools, how do good works stand out? David Wang: What truly matters in the future is not generation ability, but distribution ability. We focus more on creator communities, IP incubation mechanisms, project matching systems, global competition systems, and international distribution networks. Because no matter how good a work is, if no one sees it, it can't produce value. AI will make content production easier, but it will also make content competition fiercer. Whether a work can be discovered, spread, and continuously developed will become increasingly critical. Q10: How does an AIGC film and television work move from a one-off short film to a sustainably developed IP? David Wang: The key is shifting from "content production" to "worldview production." A good IP is not one work, but a universe that keeps growing new stories. AI lowers production cost, but the real value still comes from characters, worldview, and fan communities. The path we see is: story, community, worldview, series content, brand partnership, global distribution, then long-term IP operation. Q11: What will change in IP trading, IP incubation, and IP co-creation in the AI era? David Wang: In the past IP development was linear, with layers of barriers between creators and the public. Now it will become networked. Creators, fans, brands, and investors may all participate in IP's growth. Many future IPs may not be created by one film company, but incubated jointly by a global community. This will make IP formation more open, and will also make collaboration mechanisms, copyright mechanisms, and revenue distribution more important. Q12: After AI-generated content appears in volume, won't copyright, attribution, creator contribution, and IP ownership become more complex? David Wang: Definitely; this is a problem the industry must face. My view is that AI itself is not the creator; humans are. The future needs more transparent contribution-record mechanisms to confirm who provided the story, who provided the character design, and who participated in production. Blockchain technology may play a role in this process, because it can help record and track different creators' contributions. Only when contribution is confirmed can collaboration continue. Q13: What role do AIGC film and television competitions play in the ecosystem? David Wang: It carries four functions: talent discovery, project incubation, market education, and industry connection. Many future creators, directors, and IP projects may first be discovered in competitions. For the industry, a competition is also a filtering mechanism that lets excellent works, excellent teams, and potential partners meet faster. After AI lowers the creation barrier, how to discover good works becomes increasingly important. Q14: How do you evaluate the quality of AI content? In judging a future AIGC work, what shouldn't one only look at? David Wang: Technical effect is only the baseline. What matters more is whether the work has emotional resonance, a unique point of view, cultural value, and can be remembered by audiences. What audiences ultimately remember is never the prompt, but the story. When everyone can generate beautiful images, the real difference returns to narrative, character, rhythm, and emotional expression. Q15: Over the next three years, what will be the biggest change in the AIGC film and television industry? David Wang: I think it will be that global collaborative production becomes the norm. A future film may be jointly completed by Singaporean planning, Chinese screenwriting, Indian animators, European composers, and an American distribution team, with AI becoming the infrastructure connecting these people. What truly changes the film industry isn't making video generation faster, but giving more people around the world who once had no chance to tell stories the first chance to be heard by the world. --- Original publication: https://uniqueresearch.substack.com/p/src-20260610-01html On-site reading page: https://ffcap.cn/en/research/src-20260610-01html