The Future of Artificial Intelligence in Hollywood

Hollywood is going through a major shift as artificial intelligence becomes part of every stage of making movies and TV shows. From writing scripts and casting actors to creating visual effects and animation, AI tools are changing the way entertainment is produced. These tools help speed up the process and open up new creative ideas. Filmmakers can now use AI to save money and make difficult tasks easier, which could lead to a new and exciting era of content creation.

This article looks at how AI is currently being used in key areas of production-filmmaking, animation, visual effects (VFX), acting, and screenwriting-and what we can expect in the near future. Each section provides examples of real-world applications, with a particular focus on Luma AI and other platforms that are helping to transform both the creative and technical sides of Hollywood.

How AI Is Revolutionizing Film Production

AI is playing a growing role from the early planning stages of a movie to the final edit. Pre-production is one area where AI is being used more and more. For example, generative AI models can now create storyboards and concept art by analyzing scenes from a script or simple written descriptions. This allows directors and cinematographers to quickly visualize planned shots. Tools such as Adobe Firefly can turn text prompts into storyboard images that can be further edited in programs such as Photoshop or Illustrator.

Another new platform, Luma AI’s Dream Machine, allows filmmakers to create concept art or even short video clips simply by describing a scene in everyday language. Luma’s system works like a “visual thought partner,” allowing creators to quickly test scene ideas without the need for complicated prompts. For example, a director can say “a futuristic cityscape at sunset” and instantly get a detailed AI-generated image to adjust or share with the team. These features accelerate the pre-visualization process, helping studios develop proof-of-concept materials for new projects much faster.

Beyond storyboarding, AI also supports casting and scheduling decisions during pre-production. Platforms like Largo.ai can study actors’ past performances and compare them to character profiles from the script to suggest the best possible choices for each role. While casting decisions are still made by humans, these AI suggestions give casting directors a broader and more data-driven pool of candidates to consider.

During filming, AI-powered tools help introduce advanced methods such as virtual production. This technique uses digital backgrounds – often displayed on large LED screens – that can change in real time. A well-known example is The Mandalorian. AI enhances this method by enabling real-time scene building and rendering. This means that directors can view near-final scenes directly through the camera.

A good example is Neural Radiance Fields (NeRFs), which are changing the way 3D environments are created from video. With just a few simple scans – even with a smartphone like an iPhone – tools like Luma AI can create realistic 3D models of real locations. These models can be used as digital sets, or AI can create entirely new, imagined environments for filming.

This helps filmmakers test camera angles and lighting while they’re shooting, rather than waiting for special effects in post-production. AI can even suggest the best lighting and camera setups by analyzing the scene and matching it to the director’s style.

Another big help is markerless motion capture. Tools like Move.ai use AI and computer vision to record how actors move using regular video-without suits or special markers. These movements can be instantly turned into 3D character animations. This makes it easier to mix real actors with computer-generated elements during filming.

In post-production, AI keeps making things faster and easier. Today’s editing software includes AI tools that can automatically create rough cuts, match different shots, or pick the best takes from daily footage by analyzing facial expressions.

Color grading—which used to take a lot of time, going frame by frame—is now much quicker thanks to AI. With just one model, the software can apply a certain visual style to the whole film. Programs like DaVinci Resolve and Adobe Premiere Pro already use AI for smart color matching, finding scene cuts, and adjusting shots for different screen sizes.

On the audio side, AI tools can cleanse dialogue tracks by removing background noise and can even suggest or generate sound effects that perfectly align with on-screen events. For instance, Adobe Audition’s AI can automatically detect and level dialogue, or AIVA can compose mood-fitting background music at the click of a button.

All these new tools in film production show that we’re moving toward a future where small creative teams can achieve results that used to need large crews and big budgets. With real-time AI tools for planning and rendering, creators can now solve problems early—during planning and filming—rather than fixing them later, which can be expensive.

The whole production process is becoming more flexible and faster. The lines between planning (pre-production), filming (production), and editing (post-production) are starting to blur. For example, a director might use AI to create a rough version of a special effects scene before filming the actors. This helps guide the actual shoot.

By the time filming starts, many creative choices have already been explored with AI support. Simply put, AI is making film production more efficient and flexible, giving filmmakers more time to focus on creativity instead of technical problems.

The Role of AI in Modern Animation Workflows

Animation is one area where AI is likely to make a big impact. In some ways, it’s actually easier for AI to create animation than live-action films. That’s because animated characters and worlds are already stylized, so viewers are more accepting of small mistakes or strange details that AI might create.

As one artist said, “It’s easier to copy something that doesn’t look real than something that does.” This means that cartoon characters and fantasy creatures are a natural fit for AI. Because of this, AI can help speed up almost every part of the animation process—from the first design ideas to the final rendering.

Already, studios are using AI for visual development in animation. Instead of teams of artists drawing countless character sketches and environment paintings, a single artist can use an image generator to “spitball” dozens of ideas and styles in a day. Executives deciding whether to greenlight an animated film often want to see a clear vision of the world and characters. AI concept art helps creators get to a polished proof-of-concept faster, by generating quick iterations of character designs or entire landscapes based on simple prompts. These AI-generated images can then be refined by human artists, blending the speed of automation with human creativity. The result is a much shorter development cycle for animated projects.

AI is also changing how storyboards and layouts are made in animation. Usually, storyboard artists draw each shot of the film by hand—a process that takes a lot of time. Now, AI tools can read a script and automatically create basic storyboard frames. The artist can then adjust and arrange these frames as needed.

This doesn’t replace the artist, but it means one person with AI support can do in a few days what used to take a whole team several weeks. Sam Tung, a professional storyboard artist, said that while AI-generated images aren’t always better than human-made ones, “they’re certainly faster and, at least right now, they look cheaper.”

In the near future, animation studios may hire more AI curators—artists who guide AI tools, choose the best images, and improve them, instead of drawing everything by hand.

One of the most talked-about changes in animation is the rise of AI-generated films—complete shorts or full-length features created mostly with AI tools. In 2023, the YouTube studio Corridor Digital released “Anime Rock, Paper, Scissors,” a short film that used AI to turn live-action footage into a stylized anime look. The team filmed actors in front of a green screen, then used the AI model Stable Diffusion to repaint each frame in an anime art style. This method, known as AI-assisted rotoscoping, gave the film a hand-drawn anime feel with much less effort than traditional methods.

The creators described it as a new way to animate—turning real-life video into cartoons—and said it could make animation more accessible to creators without large budgets. They imagined a future where a small group of friends with a great idea could produce high-quality animation without needing big teams or years of work.

However, the project also sparked controversy. Some animators said the style was copied from real anime artists, since the AI was trained on their work. Critics argued that while the method saves time, it raises ethical concerns about using other artists’ styles without permission.

Still, the project showed how the future of animation may blend human creativity with AI tools, speeding up the process and opening doors for more creators.

We’re now seeing announcements of full-length animated films made with the help of AI. One well-known example is Critterz, a short film from 2023 that was promoted as the first to combine OpenAI’s image generator DALL·E with traditional animation techniques. Critterz featured a cast of AI-designed monster characters and was shown at major festivals like Annecy and Tribeca. It even won a Producers Guild Innovation Award for its creative approach. Thanks to the success of the short, the team is now turning Critterz into a full-length CG animated film, with a script written by professional screenwriters and support from a large UK-based studio.

This move—from an AI-assisted short film to a studio-supported feature—shows how fast AI tools are improving in animation. Another example is Where The Robots Grow (2024), directed by Tom Paton, which is being called the world’s first AI-animated feature film. It was made by a very small team of just nine people, using AI for most of the work.

In India, one filmmaker created a 95-minute animated film on a very low budget, using more than 30 different AI tools. He handled everything—from designing characters and creating backgrounds to simulating drone-style camera shots—almost completely through AI, with very little help from a crew.

These early projects aren’t perfect. Animators still notice problems, like characters changing slightly between scenes or lip-syncing that doesn’t always match. But the technology is improving very quickly. One filmmaker even said that the tools they used were already outdated after six months, and that if they made the same film today, it would be “a thousand times better.”

This shows clearly that the quality gap between AI-generated and traditional animation is closing fast.

Looking to the future, AI could take over some of the more time-consuming parts of animation. This includes tasks like in-betweening (drawing the frames between key poses), cleaning up line drawings, and applying color and shading that stay consistent from frame to frame.

There are already experimental tools that can take a rough animation sketch and turn it into a fully colored frame that matches the production’s style. This would allow human animators to focus more on key creative tasks—such as drawing main poses and developing the story—while AI handles the repetitive work in real time.

AI could also help bring new life to older animations. For example, machine learning could be used to upscale classic cartoons to higher resolutions or make low-frame-rate animations smoother—without losing the original hand-drawn feel that makes them special.

The future of AI in animation seems to have two main paths: democratization and augmentation. It’s democratizing because more people can now create animated stories without needing a big studio. Even a solo creator could dream up and produce an animated film.

At the same time, for professional studios, AI acts as a support tool. It speeds up the workflow and reduces costs. We’ll likely see more mixed productions, where AI does about 80% of the routine work, and artists focus on the final 20%—the parts that need real human skill or creative thinking.

Many creators hope this mix will lead to a wave of new animated content. Wild styles and stories that were once too costly or difficult to animate could now become possible.

But there’s also a warning from the animation community. Some fear that if studios rely too much on AI, it might copy what already exists instead of helping people create something new. As one animator said, depending on AI’s output could lead to “just repeating old characters instead of inventing something original.”

The real challenge will be to balance AI’s efficiency with true creativity—and to respect the work of human artists who came before. If done right, AI can become another powerful tool in the animator’s toolbox, helping the art form reach new levels.

AI-Powered Visual Effects: Faster, Cheaper, Smarter

Nowhere is the impact of AI more visible—quite literally—than in the world of visual effects. Today’s big-budget films use VFX for everything from building alien worlds to making actors look younger. AI is now helping to make many of these processes faster and more efficient.

Traditional VFX work includes time-consuming tasks like rotoscoping (tracing actors frame by frame) and compositing (combining different visual elements into one scene). These detailed and repetitive jobs are exactly where machine learning is especially useful, as it can help automate them quickly and accurately.

Today’s AI tools can do rotoscoping much faster than humans. For example, Runway ML and Adobe’s AI-powered features in After Effects can automatically detect people or objects in a video and create accurate masks that follow them in every frame. This means VFX artists no longer have to draw outlines by hand around a moving actor to separate them from the background—the AI recognizes the actor and does it automatically.

This allows artists to replace backgrounds or add CGI elements much more quickly. AI is also useful for removing unwanted objects. For example, things like boom microphones or even entire crowds can be erased using tools like Adobe’s Content-Aware Fill for video, which uses machine learning. The AI studies the surrounding pixels and guesses what the scene should look like without the object, then fills in the space—often with impressive results.

Besides speeding up traditional VFX tasks, AI is also opening up new possibilities for creating digital environments and characters. Generative models can now produce high-quality textures, landscapes, and even 3D models from scratch, which artists can then improve and fine-tune.

As mentioned earlier, NeRF technology—developed by companies like Luma AI—can turn video into 3D scenes. This becomes especially useful in VFX when the scenes are imaginary or highly edited. Instead of building a detailed environment by hand, an artist can give concept art or a few reference images to an AI and get a photorealistic 3D scene to work with.

For example, if a film needs an ancient city for a wide aerial shot, the AI can generate a believable city view from a short description or a few pictures. The VFX team can then adjust the result and blend it into the real footage. This makes it much faster to build background elements that used to take weeks.

Character effects and simulations are another area getting an AI boost. Simulating realistic water, fire, or crowd behavior can be computationally expensive. Researchers are exploring AI models that learn the physics of these phenomena from data, so they can produce plausible simulations much faster than traditional physics engines. That means things like explosions, smoke, or massive battle scenes with thousands of soldiers could be generated in a more automated way, guided by AI that has learned how these look in the real world or in prior simulations. Early versions of this are in use: some studios employ AI upscaling on low-resolution simulation outputs to add detail, rather than running a full high-res sim.

One of the most eye-catching uses of AI in visual effects is creating digital humans—especially for de-aging, face replacement, or fully synthetic actors (we’ll cover acting in more detail in the next section). Companies like MARZ (Monsters Aliens Robots Zombies) have built AI systems for what’s known in the industry as “Vanity VFX”—effects used to make actors look younger or change their appearance.

Vanity AI, MARZ’s own tool, was used in recent Marvel projects to realistically de-age actors and even fix lip-sync problems when dialogue was changed after filming. Instead of having a team of artists edit each frame by hand to smooth wrinkles or adjust hair color, the AI applies changes across all frames, and artists only need to refine the final result.

A well-known example of AI de-aging is Indiana Jones and the Dial of Destiny (2023), where 80-year-old Harrison Ford was made to look like he was in his 40s during long flashback scenes. While Disney hasn’t said exactly which tools were used, the process clearly involved AI face mapping and reconstruction due to the large amount of footage.

Similarly, in The Irishman (2019), directed by Martin Scorsese, custom machine learning tools helped de-age Robert De Niro and other actors without using facial tracking markers. The result blended naturally with their performances on screen.

Deepfake technology—once just a hobby for internet users—has now become a serious tool in Hollywood visual effects. A startup called Deep Voodoo, supported by filmmakers Trey Parker and Matt Stone, is leading the way in using deepfake tech for real movie productions.

This kind of face-swapping AI isn’t just used to bring back late actors, like Peter Cushing in Rogue One: A Star Wars Story. It can also help with action scenes and reshoots. For example, when a stunt performer does a dangerous scene, AI can replace their face with the lead actor’s face in every frame. This makes it look like the actor did the stunt themselves. Older VFX methods could do this too, but deep learning makes the final result more realistic by keeping natural facial expressions and lighting details.

This not only makes filming safer—since actors don’t have to do risky stunts—but can also reduce costs by avoiding complex makeup or full CG face replacements.

Another use is for changing dialogue after filming. If a director wants to adjust a line, studios can now use AI to change the actor’s lip movements to match the new audio. They can even generate the actor’s voice saying the new line—all without needing to bring the actor back on set.

Looking ahead, full AI video generation may soon blur the line between production and visual effects. Tools like Runway’s Gen-2 and Gen-3 can already create short video clips from just text prompts—basically generating footage from nothing.

Another big step forward is Luma AI’s new model, Ray 2, which can produce up to 10 seconds of realistic, cinematic video from a simple prompt or even a single image. Early demos of Ray 2 have impressed people with how smooth the motion looks and how well the clips follow real-world physics.

These tools aren’t yet ready to create final movie scenes like those in Hollywood blockbusters. They’re still limited to short clips and sometimes have visual flaws. But the direction is clear. In the next few years, a director might be able to say, “Give me a sunset car chase on the Golden Gate Bridge,” and receive a rough version from the AI. The VFX team could then polish it and combine it with scenes of real actors shot on green screen.

This could greatly speed up how films are made—and even allow fully AI-generated scenes for planning or background shots. Luma AI says its goal is to build a “universal imagination engine” that can create any video idea, from early storyboards to final visuals. With tools like Dream Machine and Ray 2, they’re moving closer to that future, giving filmmakers a powerful new way to bring ideas to life with just words.

Despite these gains, human VFX artists are far from obsolete – if anything, their expertise is even more crucial to guide and correct AI. Artists often talk about the final 10% of a VFX shot taking 90% of the time; AI might get you to 90% completion in moments, but that last polish still needs an artist’s eye. The future likely holds a workflow where AI handles the grunt work (tracking, rotoscoping, initial composites, draft simulations) and artists spend more time on creative decisions and fine-tuning. We may also see new job roles emerging, like AI VFX supervisors who specialize in knowing which models to use and how to train or prompt them for the desired outcome. And importantly, with AI doing more, visual effects could become more budget-friendly, enabling independent filmmakers to realize ambitious ideas that previously only big studios could afford. Indeed, industry observers note that AI is making Hollywood production more cost-efficient – a recent analysis projected a 75% increase in AI usage in content creation by 2025, as studios seek the competitive edge of faster, cheaper VFX.

AI and Acting: Digital Doubles, Voice Cloning & Performance Capture

Acting is a deeply human art form – the emotion in a performer’s eyes or the timbre of their voice can make or break a scene. It might seem, then, that AI has little role to play on the stage compared to behind the camera. And indeed, AI won’t be winning Oscars for Best Actor anytime soon. However, AI is increasingly influencing who (or what) we see on screen and how performances are crafted and preserved. In Hollywood today, AI touches acting in two major ways: casting/character creation and performance augmentation, which includes digital doubles, de-aging, and voice cloning.

In terms of casting, we’ve already talked about how AI tools can suggest real actors for roles by analyzing certain traits. But AI can go even further—it can create completely new “virtual actors.” These are also known as synthetic performers—digital characters that aren’t based on real people, but are fully generated by AI.

So far, these synthetic actors have mostly appeared in video games or as virtual influencers on social media. But we’re getting close to seeing them in movies, too. For example, a background character in a crowd scene could be an AI-generated person instead of a human extra—and most viewers wouldn’t even notice. With AI, a director could fill a medieval marketplace with thousands of unique-looking townspeople without hiring extras or modeling each one by hand. The AI makes sure that no two faces look exactly the same.

Naturally, Hollywood actors are paying close attention to this trend. The actors’ union, SAG-AFTRA, has created new contract rules: if a synthetic performer is used instead of a human actor, the union must be informed and given the chance to negotiate fair pay for the person being replaced.

In other words, if a studio tries to use an AI avatar instead of hiring a background or speaking actor, it becomes a legal issue. These rules show that full AI actors aren’t common yet in 2025—but the industry is clearly preparing for that future.

More common right now is the creation of digital replicas of real actors. This could be as simple as a high-resolution 3D scan of an actor’s face and body, which can then be used to render that actor under different conditions. For instance, a stunt scene might employ a digital replica for dangerous moments (a CG double), or a franchise might use an older scan of an actor to recreate their younger self in a flashback. We’ve seen striking examples: Star Wars brought back a young Luke Skywalker in The Mandalorian and The Book of Boba Fett using a combination of CGI and deepfake AI, allowing Mark Hamill’s 70-year-old likeness to appear as his 30-something Luke. Similarly, the late Carrie Fisher and Peter Cushing were “revived” in Rogue One through digital doubles. These feats relied on artists, but also on AI algorithms for facial motion capture and blending that made the illusions convincing.

AI-based performance tools are also being used to change an actor’s performance after filming. As mentioned earlier, de-aging is one example—digitally smoothing an actor’s face, frame by frame, to make them look younger. Another powerful use is voice cloning. With AI, studios can now recreate an actor’s voice, which has major implications.

In 2022, legendary actor James Earl Jones gave Lucasfilm permission to use AI to copy his voice for Darth Vader. A Ukrainian company called Respeecher trained an AI model on past recordings of Jones’s voice. This allowed new Darth Vader lines in the Disney+ series Obi-Wan Kenobi to sound just like Jones in his prime. Jones approved the use—he is now retired—showing how AI can help continue a character’s legacy even when the original actor steps away.

Another example is Val Kilmer in Top Gun: Maverick (2022). After losing his voice due to throat cancer, Kilmer’s few lines as Iceman were created using AI trained on recordings of his real voice. This gave the scene emotional weight that might not have come from a different voice actor.

These voice clones are like the audio version of a digital double. But they also raise important questions—can an AI voice truly match the emotion of a human one? For now, the technology works best when guided by a real performance. For example, an impersonator or the actor (if able) delivers the line, and the AI changes the voice to match the original actor.

In the future, we may hear voices of actors who are no longer alive, brought back by AI. To address this, SAG-AFTRA has created rules: studios must get permission from actors or their estates to create digital versions of their voice or appearance. That permission must clearly explain how the AI version will be used. In short, actors are beginning to license their digital selves.

AI’s influence on acting also appears in dubbed and localized performances. For international releases, AI can not only translate and generate dialogue in different languages, but also adjust the on-screen actor’s lip movements to match the new language. Companies like Flawless AI do exactly this – using a combination of deepfake tech and CG, they alter the actor’s mouth in each frame so that, for example, an English-speaking actor appears to be naturally speaking Japanese in the dubbed version. The result is a far more immersive experience for local audiences and could make dubbing more acceptable than subtitles in many markets. This kind of AI-driven lip sync, paired with high-quality voice cloning in multiple languages, means an actor’s single performance can be seamlessly translated and presented worldwide as if they themselves acted in every language.

What about replacing actors completely? While the idea of a fully AI-generated lead actor still sounds like science fiction, some early experiments are already happening. In 2022, a drama called b AI (believe AI) was announced, reportedly starring an AI-powered humanoid robot in the lead role—a kind of advanced animatronic with AI features.

In video games and virtual reality, AI is already being used to power interactive NPCs (non-player characters) that respond with realistic dialogue and behavior. These characters are getting closer to feeling like real, autonomous beings. It’s not hard to imagine a future movie where a lifelike AI character appears on screen next to human actors—an evolution of CGI roles like Gollum or Thanos, but driven entirely by AI instead of motion capture by an actor.

If that happens, the rules for Synthetic Performers set by SAG-AFTRA will be put to the test. According to the latest agreement, studios must get permission and provide fair pay if they use a synthetic performer based on a real actor’s face or likeness—even if they just use the actor’s face as a prompt.

These rules are meant to stop studios from training AI models on famous actors and creating lookalike performances without consent—a scenario that AI could soon make possible.

For now, the most practical use of AI in acting is helping real actors do things that would normally be impossible. Need an actor to appear younger? AI can de-age their face—and even their voice. Need the same actor in two places at once? You can scan them and use a body double with AI face replacement for the second scene. Want to bring back a legendary actor who has passed away? With enough footage and permission from their estate, an AI version could appear in a cameo. This was even considered for a James Dean role a few years ago.

These tools are exciting—but also raise serious questions. Many actors worry they might be giving away more than just their image. Are they handing over the soul of their performance to an algorithm?

The creative industry is now working hard to set clear limits. The general view is that AI should support and preserve human performances—not replace them. For example, using AI to help an aging actor continue playing a beloved role (like James Earl Jones as Darth Vader) is often seen as a respectful use of the technology. But using AI to avoid hiring actors at all is much more controversial.

In the near future, we’ll likely see more actors actively working with AI instead of resisting it. Big-name actors might get full-body and voice scans of themselves and license their digital avatars for specific projects—letting them “act” without ever being on set. They could perform using motion capture in a studio, while their AI double appears in a movie filmed anywhere in the world.

Actors might also use AI to help with preparation. Imagine an AI tool that can play the role of a scene partner, letting an actor rehearse alone in a virtual space. AI could even give feedback on a performance—though some actors may not like taking direction from a machine!

Casting could also change. AI might scan thousands of online videos to find new talent with the exact look, voice, or style a role needs—something that’s hard for human casting teams to do on their own.

AI in Scriptwriting: From Story Generation to Dialogue Polishing

In the past few years, generative AI tools like OpenAI’s GPT models have made it possible to create story ideas, dialogue, and even full screenplay drafts with just a simple prompt. For writers in Hollywood, this is both exciting and a little unsettling. On one hand, AI offers new ways to brainstorm and beat writer’s block. On the other, it brings up questions about who really owns the writing and whether the ideas are truly original.

Today, many writers use AI in a small but useful way—as a smart brainstorming assistant. For example, if a writer is stuck on a scene, they might ask a tool like ChatGPT, “How might two estranged siblings argue in a hospital waiting room?” The AI can quickly generate a bit of dialogue or a scene idea. The writer probably won’t use it exactly as written (and usually shouldn’t, since AI often produces bland or clichéd lines), but it can offer inspiration or a new direction the writer hadn’t considered.

Writers also use AI to explore plot options. A prompt like “Give me five different motivations for the villain in act two” might reveal new twists or story paths. In this way, AI becomes a creative partner—available anytime, ready to suggest ideas without judgment.

AI is also helpful for everyday writing tasks. It can summarize scenes, build character backstories, or turn regular text into screenplay format. For example, it might take a paragraph of story and rewrite it as a properly formatted script scene, complete with slug lines and dialogue—saving time on formatting and structure.

AI can now do more than just help with ideas—it can also write full pages of a script. Some production companies have even tested AI by asking it to write short film scripts, which were then filmed by human crews. The results are often a bit strange or repetitive. Since AI learns from existing books and movie scripts, it tends to remix what it has seen before. For example, an AI-generated script might combine common movie themes in a way that feels familiar but lacks real originality or emotional depth.

Still, the technology is getting better. With the right prompts and human editing, some of the results are becoming more useful. Thanks to advances in natural language processing (NLP), AI can now follow a story over a long document, making it possible to keep track of a full movie-length plot.

Filmmakers are already using AI for tasks like script coverage and analysis. This means putting a script into an AI system to get a short summary and basic feedback. Normally, interns or story editors do this job—reading a script and writing notes—but an AI can produce a quick version in seconds. It might point out things like “the main character doesn’t have a clear goal by page 30” or “multiple scenes follow the same pattern.” When combined with a human review, this kind of feedback can help writers improve their drafts more efficiently.

Several AI-powered writing tools have been created to support creative writing. Besides the popular ChatGPT, there are others like Jasper, Sudowrite, Scalenut, and Writesonic. Some writers use these tools to speed up their writing process. These platforms can produce surprisingly clear and structured story text, and they can be guided by specific prompts or styles—for example, “write a scene in the style of a Marvel action-comedy.”

Some tools even include features designed for storytelling, like keeping a character’s voice consistent or helping connect two parts of a plot. But there are still limits. AI doesn’t truly understand emotions or deep themes. It works by recognizing patterns from what it has seen during training. As a result, it often repeats clichés. For example, many AI-written motivational speeches end with lines like “because together, we are unstoppable.”

If a writer relies too much on AI-generated text, the story may lose originality. There’s also the risk of confusion in longer scripts. While AI might do well with short scenes, it can lose focus in a full-length screenplay, leading to plot holes or characters acting out of character.

The Writers Guild of America (WGA) has taken clear steps to deal with the rise of AI in screenwriting. In its 2023 contract talks, one major decision was to say that AI-generated content is not considered “literary material” or “source material.” This means if a studio gives a writer AI-generated pages to revise, the AI doesn’t get credit—and the writer’s credit is fully protected. AI is treated like a tool, not a co-writer.

The agreement also says that writers can choose whether or not to use AI in their work. Studios cannot force writers to use AI as a condition of their job. However, if a writer does use AI help, they have to tell the studio if asked—so there’s no hidden use of AI in the process.

These rules make it clear: the writer is still the main creative voice, and AI is just a tool—like a spellchecker or a thesaurus, though much more advanced.

In the near future, AI will likely become a regular part of the writing process. Writers might use it to create first drafts, which they then revise and improve. You can think of this as a more advanced version of outlining—the AI provides a basic structure, and the human writer adds real dialogue, emotion, and creative detail.

This could be especially helpful for scripts that follow a set formula, like episodes of crime or medical dramas. A showrunner might ask AI to create a rough plot for a weekly case, while the writing team focuses on building strong characters and adding humor or emotion.

AI could also be useful in interactive storytelling—projects like video games or choose-your-own-adventure stories, which need many different versions of the same scene. AI could quickly write these variations, while writers review and guide the content to make sure it stays consistent with the overall story.

AI might also be used to help with continuity and canon management. In big franchises with lots of backstory—like Marvel or Star Wars—an AI could be trained on all past scripts, episodes, and related media. It would act like a smart assistant, helping writers avoid mistakes or contradictions.

For example, the AI could answer questions like, “Has this weapon been used before in the series?” or “Which episodes had a similar storyline?” This kind of support would be especially useful in writers’ rooms, where keeping track of complex story worlds can be difficult. With AI’s help, teams could make sure their stories stay consistent and accurate across many films or episodes.

Even with all these advantages, the true creative spark—the ability to invent new stories and explore deep emotions—still belongs to human writers. AI can mix and match ideas, but it doesn’t create the way people do. It doesn’t have life experience or a personal message to share.

The hope is that AI will take care of repetitive tasks—like brainstorming basic ideas, formatting, or remembering small details—so that writers can spend more time on the creative work that only they can do.

In fact, some Hollywood writers are already starting to see AI as a helpful partner, not a threat. For example, the animated show South Park recently had an episode where part of the script was written using ChatGPT, as a kind of meta-joke. They even listed “ChatGPT” in the end credits as a co-writer—just for fun.

It’s a sign of the times: AI is entering the writer’s room, even if it’s just the intern for now.

The film industry will likely face some challenges as AI becomes more common in writing. There are real concerns—like plagiarism (since AI might accidentally copy lines from its training data), questions about credit (who gets recognized if an AI writes a great joke?), and the risk of studios using AI to avoid hiring writers, something the Writers Guild is actively pushing back against.

Still, the creative community is paying close attention. With the right rules and cooperation, AI will probably be used to support writers, not replace them. Maybe in the future, a blockbuster movie will list both a human and an AI as co-writers—but only if the human chooses to use AI and directs the process from start to finish.

Like in many other industries, the future of AI in screenwriting looks like a partnership: combining human creativity with AI’s speed and efficiency. Together, they might help bring to life stories we’ve never seen before.