The teleserye machine has entered tiktok

By Noel Galon de Leon

I have been thinking about the sudden popularity of AI-generated serial videos on TikTok, not simply as another passing internet trend, but as something that tells us an uncomfortable truth about the way we consume stories today. The videos can be strange, repetitive, visually awkward, and sometimes almost absurd. Their characters may look too polished, too artificial, or strangely human. Their voices may sound synthetic, and their plots can be predictable. Yet people keep watching. They ask for the next episode. They argue about the characters. They demand revenge, reconciliation, betrayal, romance, or another twist. They share the videos with friends and wait for Part 2, Part 3, Part 4, and sometimes Part 20. I find this fascinating because the real story may not be the AI video itself. The real story is us. These videos reveal something about what Filipino audiences have always wanted from storytelling and what digital platforms have learned to give us with astonishing efficiency.

I think the first mistake is to assume that Filipinos suddenly became interested in AI storytelling simply because AI is new. We did not suddenly discover serialized storytelling when generative AI arrived. We have been living with serialized narratives for generations. We grew up with radio dramas, komiks, serialized novels, afternoon and primetime teleseryes, fantasy programs, melodramatic films, Wattpad fiction, Facebook stories, and now TikTok episodes. We understand the grammar of serialization almost instinctively. Give us a character with a problem, introduce an obstacle, complicate the relationship, reveal a secret, and end just before the resolution. We know what to do next: we watch another episode. The AI has not invented this appetite for serialized stories. It has simply found a faster and cheaper machine for feeding an appetite that has already been deeply established by decades of Filipino popular culture.

This is why I hesitate whenever I hear people describe these videos as merely “AI content.” That phrase is too broad to explain what is actually happening. What we are witnessing is closer to the industrialization of serialized storytelling. AI makes it possible to produce characters, environments, voices, dialogue, movement, and scenes without the traditional production apparatus required by television or film. A creator does not necessarily need a studio, a cast, a location, expensive equipment, or a conventional post-production team. The barrier between having an idea and publishing an episode has become dramatically thinner. This matters because once production becomes cheaper and faster, stories can be produced in greater volume. And when stories can be produced in greater volume, creators can experiment constantly with different characters, conflicts, emotional hooks, and cliffhangers to discover what makes people stop scrolling and continue watching.

TikTok is particularly suited to this transformation because the platform does not ask viewers to commit to a two-hour film or a forty-five-minute television episode. It asks for a few seconds of attention, and that creates a very different cultural arrangement between storyteller and audience. The creator’s first responsibility is no longer simply to tell a good story. The creator must first survive the scroll. The opening seconds become a battlefield in which attention has to be captured almost immediately. Something has to happen: there must be a question, a conflict, a shocking image, an unusual character, a surprising statement, or an emotional provocation. The story must then move quickly enough to prevent the viewer from leaving. At the same time, the episode must provide enough information to create emotional investment while withholding enough information to make the viewer curious about what comes next. The result is storytelling shaped not only by narrative needs but also by the architecture of the platform itself.

This is where the cliffhanger becomes almost a technological device. “To be continued” is no longer merely a narrative technique; it is also an engagement mechanism. A story can now be deliberately structured around the desire to make the audience wait. The unfinished story becomes more valuable than the finished one because the unfinished story produces another view, another comment, another share, another follow, and another opportunity for the algorithm to circulate the content. The narrative and the platform’s economic logic begin to resemble each other because both depend on continuation. The story has to remain unresolved long enough to encourage another click, while the platform has to keep the viewer engaged long enough to generate another measurable interaction. In this environment, suspense is no longer only an artistic choice. It can also become part of the machinery of attention.

This is also why Filipino audiences may be particularly receptive to the format. We are already deeply familiar with emotional excess and the language of the teleserye. We understand the importance of family secrets, forbidden relationships, social class, betrayal, revenge, poverty, ambition, sacrifice, redemption, and impossible love. We do not necessarily require a story to be subtle before we become emotionally invested in it. Sometimes we enjoy a story precisely because it gives us emotions in concentrated form. The AI-generated serial video understands this perfectly, whether intentionally or accidentally. It compresses melodrama into a few minutes and delivers it directly to the palm of the viewer. What television once stretched across weeks or months can now be compressed into dozens of short episodes, each designed to produce a small emotional shock and then immediately create the desire for another one.

There is something almost comic about watching an AI-generated character suffer through an impossibly dramatic situation while thousands of viewers respond as though they are watching a real television drama. But I do not think the joke should be entirely on the audience. We should ask why we become emotionally invested in fictional characters in the first place. We have always cried over invented people. We have always hated villains who never existed. We have always defended characters as though they were members of our own families. The artificiality of the AI character does not necessarily prevent emotional engagement. If anything, it exposes how much of storytelling depends on structures of expectation. Give us a recognizable conflict, a familiar emotional situation, and a character we can identify with, and we will often supply the emotion ourselves. The machine does not have to feel anything for the audience to feel something.

The comments are perhaps even more interesting than the videos themselves because audiences do not merely consume these stories. They participate in them. They choose sides, demand changes, predict what will happen, criticize characters, ask creators to bring someone back, and request another twist. In some cases, the audience becomes an informal writers’ room. The story is no longer entirely produced before publication; instead, it develops through an ongoing conversation between creator, audience, platform, and algorithm. This creates a form of participatory storytelling in which the distinction between production and reception becomes increasingly difficult to maintain. The audience is no longer simply at the end of the communication process. Its reactions can become part of the mechanism through which the next episode is imagined, produced, and distributed.

This changes the old relationship between author and reader. Traditionally, the writer creates a work and the reader encounters it afterward. There may be interpretation, criticism, fan fiction, discussion, and response, but the original work remains relatively stable. In TikTok serial storytelling, the boundaries are more fluid. Audience reactions can influence what happens next. A creator can observe which character receives the strongest reaction and then give that character more screen time. A villain can become popular and suddenly become central to the story. A minor character can become a favorite. The comments can effectively become market research conducted in public. What used to happen through private editorial decisions, focus groups, ratings, or audience surveys can now happen visibly beneath the story itself, with viewers directly telling creators what they want to see.

That is where I become both fascinated and uneasy. When storytelling is continuously adjusted according to audience reaction, what happens to artistic intention? What happens to surprise? What happens to the unpopular but necessary part of a story? Literature, at its best, does not always give us what we want. Sometimes it gives us what we did not know we needed. A serious novel may bore us before it changes our understanding of the world. A poem may resist immediate comprehension. A film may refuse to provide closure. A difficult story may force us to remain uncomfortable. But algorithmic storytelling operates under a different pressure. It rewards what keeps people watching, and this creates a fundamental tension between the demands of sustained attention and the freedom to make artistic choices that may initially confuse, frustrate, or even repel an audience.

This creates a potential conflict between storytelling as art and storytelling as optimization. The danger is not that AI will suddenly destroy literature. That sounds too simplistic. The more immediate danger is that we may gradually become accustomed to stories that are engineered primarily for continuation. We may begin to measure narrative success through views, retention, comments, shares, and episode requests. The story becomes a performance metric. The character becomes an engagement device. The cliffhanger becomes a business strategy. Emotion becomes data. When these measurements become the dominant way of evaluating whether a story is successful, the storyteller may begin to make decisions based less on what the story requires and more on what the platform rewards.

And yet, I cannot dismiss these videos simply as inferior entertainment. Doing so would be intellectually lazy. Popular culture has always been dismissed by cultural elites before eventually becoming an important object of study. We should not assume that something is culturally insignificant simply because it is popular, technologically strange, or aesthetically imperfect. The correct response is to look more carefully at what these stories are doing, why audiences respond to them, and what they reveal about contemporary culture. Even awkward or repetitive AI-generated videos can tell us something important about our changing relationship with narrative, technology, attention, and one another. Their cultural value may not necessarily lie in their artistic quality but in what they reveal about the conditions under which stories are now being produced and consumed.

What interests me most is the possibility that AI-generated serial storytelling may become a new form of vernacular storytelling. The technology may be global, but the stories can still become local. Imagine AI-generated dramas written in Hiligaynon, Kinaray-a, Cebuano, Waray, Ilokano, or other Philippine languages. Imagine stories built around local neighborhoods, local folklore, local humor, local family structures, local anxieties, and local histories. Imagine a young creator in a provincial community being able to produce a serialized story using the language spoken at home and share it with an audience that would never have been reached through conventional television or publishing. The same technology that can produce an endless supply of generic stories could also potentially give smaller language communities new tools for creating and circulating narratives.

That possibility is important to me because I have always believed that the question of technology cannot be separated from the question of language. If AI storytelling becomes dominated by English and globally standardized narrative formulas, then we may simply reproduce another form of cultural centralization. We will have more content but not necessarily more cultural diversity. We will have more stories but perhaps fewer voices. The technology may appear democratic because production has become easier, but the cultural consequences will depend on whose languages, experiences, histories, and imaginations are actually represented. If the tools become widely accessible but the stories continue to come primarily from dominant cultural centers, then technological access alone will not be enough to create genuine diversity.

The real opportunity, therefore, is not simply to ask whether AI can produce stories. Of course it can. The more important question is: Whose stories will it produce? If Filipino creators use AI merely to imitate Hollywood plots, Korean dramas, American influencers, or generic internet melodrama, then we will have gained a production tool without necessarily gaining cultural independence. But if creators use the technology to tell stories that have historically struggled to reach audiences because of production costs, language barriers, geographical distance, or limited institutional support, then AI becomes more interesting. It can potentially democratize not only production but also representation. The difference lies not in the technology itself but in the cultural choices made by the people who use it.

There is another uncomfortable issue here: labor. When I watch an AI-generated serial video receive millions of views, I cannot help thinking about the people whose work traditionally makes storytelling possible. Writers, actors, illustrators, animators, cinematographers, editors, voice artists, musicians, designers, and countless other workers have spent decades building the entertainment industries we know. AI threatens to make some of these forms of labor less visible or less economically valuable. The fact that a story can now be produced cheaply does not mean that the human labor previously required to make stories should become culturally irrelevant. Behind every familiar form of entertainment is an ecosystem of people whose creative and technical work gives stories their texture, emotion, rhythm, sound, movement, and human presence.

This is why I am wary of the celebratory narrative that AI has “democratized creativity.” It has certainly lowered some barriers. But lowering the cost of production is not the same as democratizing culture. If the platforms still determine visibility, if algorithms still favor particular formats, if creators must constantly produce content to remain visible, and if audiences are trained to expect endless free entertainment, then power has not necessarily disappeared. It may simply have moved. The tools may have become accessible to more people while the systems that determine attention remain concentrated in the hands of a relatively small number of platforms. In that sense, technological accessibility and cultural power are not necessarily the same thing.

The AI video may look democratic because anyone can make one. But the larger system decides which ones become visible. That distinction matters because visibility is now one of the most important forms of cultural power. A creator can produce an extraordinary story and still disappear beneath an endless stream of content if the platform does not distribute it widely. Another creator can produce something formulaic but highly optimized for the algorithm and reach millions of viewers. This means that the future of storytelling will not be shaped only by what creators are capable of making. It will also be shaped by the invisible systems that decide what audiences are likely to encounter, watch, share, and remember.

This is why the rise of AI-generated serial storytelling deserves more serious attention in the Philippines. It is not merely about funny videos, weird characters, or another strange chapter in the history of TikTok. It is about the convergence of three powerful forces: our longstanding appetite for serialized drama, the extraordinary accessibility of generative AI, and the platform economy’s obsession with continuous attention. These forces are coming together at a moment when Filipino audiences are already accustomed to moving rapidly between different forms of media. Television, Facebook, YouTube, Wattpad, streaming platforms, and TikTok have all contributed to an environment in which storytelling is increasingly fragmented into shorter and more immediately accessible forms.

The result is a new storytelling machine, and we are already inside it. We are not simply observing this transformation from a distance. We are participating in it every time we watch, comment, share, follow, or ask for another episode. The machine learns from our behavior, and our behavior helps shape what the machine produces and distributes. In this sense, the audience is not outside the system. We are part of the system. Every click becomes a small signal about what holds our attention, what makes us curious, what makes us angry, and what makes us return. The future of digital storytelling will therefore be shaped not only by technological development but also by the habits we collectively develop as audiences.

I do not think the answer is to tell people to stop watching. People will watch what entertains them, and they should be allowed to enjoy even the strangest forms of digital storytelling. The better response is to become more conscious viewers. We can enjoy the absurdity while asking who made it, how it was made, why it was designed that way, what cultural assumptions it reproduces, and what happens when an algorithm becomes part of the storytelling process. These questions do not require us to reject technology or popular entertainment. They simply ask us to recognize that entertainment is never entirely neutral. The stories we consume shape our expectations, our ideas about characters and conflict, and even our understanding of what a story should look like.

For writers, artists, teachers, publishers, and cultural workers, the challenge is even greater. We should not simply complain that AI stories are replacing “real” stories. We should enter the conversation. We should experiment with the technology while defending human imagination, language, cultural memory, authorship, and creative labor. We should explore what AI can do without allowing it to dictate what storytelling ought to become. More importantly, we should ask how these tools can be used to strengthen rather than weaken local literary cultures. If AI can help writers work across languages, help communities preserve stories, help artists experiment with new forms, or help creators reach audiences beyond traditional institutions, then there are possibilities worth exploring. But those possibilities require cultural responsibility, not technological enthusiasm alone.

Because the most provocative question is not whether AI can write a teleserye. It is whether we will allow the logic of the algorithm to decide what a story is supposed to be. A story should not exist merely because it can be optimized for retention, and a character should not matter only because audiences are willing to click on the next episode. Storytelling has always involved uncertainty, experimentation, failure, surprise, and the possibility of giving audiences something they did not expect. If we allow algorithms to determine too completely what deserves to be told, then we risk narrowing the imagination even as we expand the quantity of content available to us.

For now, the Filipino audience is watching. We are clicking Part 2. We are waiting for Part 3. We are arguing in the comments. We are laughing at the strange faces and synthetic voices, then coming back for another episode. The attraction is obvious because the stories understand something fundamental about serialized entertainment: once we become emotionally invested, we want to know what happens next. But the larger question is what happens to us when our desire for continuation becomes the central resource of a technological system. Perhaps the most revealing thing about the AI storytelling boom is not that machines have learned how to imitate our stories. It is that they have learned how to exploit our desire to hear what happens next. And once a machine learns that desire, the story may never have to end.

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Noel Galon de Leon is a professor at the University of the Philippines Visayas. His poems have been recognized by the Don Carlos Palanca Memorial Awards for Literature. He serves as Secretary and a member of the NCLA Executive Council of the NCCA.