For decades, the industry operated one-dimensionally, with large production houses controlling access to expensive cameras and movies requiring hundreds of crores in investment, large crews and years of execution. But the rise of generative AI has begun to challenge this model.
A case in point is JioStar’s AI adaptation of Mahabharat, which clocked 6.5 Mn views on the very day it debuted. Meanwhile, Studio Blo, an AI-native filmmaking lab & studio, collaborated with filmmaker Rajkumar Hirani on an AI-native branded film for Bajaj Group. The plan is to use AI for facial cloning, voice recreation and visual storytelling.
Now, as AI-native studios emerge and filmmakers embrace generative tools across the production cycle, stakeholders are reimagining how films are conceived, produced and distributed.
“AI is helping us with new formats of storytelling. It is no longer just about automating repetitive work. It has begun to alter who gets to tell stories, how ambitious those stories can become and how entertainment gets produced at scale,” said Vijay Subramaniam, the founder and group CEO of Collective Artists Network, the creators of AI Mahabharat on JioStar.
With AI penetrating the filmmaking workflows, how is it changing the way films are made? Let’s find out…
AI Becomes Assistant Director
Today, filmmakers are increasingly creating AI-native productions, where large parts of a film are generated, modified and enhanced using generative AI models. Storyboarding and pre-visualisation have also emerged as some of the earliest large-scale AI use cases.
Vikrant Patankar, a 26-year-old independent filmmaker, said he primarily uses AI for writing and iteration. He uses Claude Sonnet extensively to refine scripts, scenes and dialogue through repeated collaborative drafts instead of accepting AI-generated outputs at face value.
Meanwhile, production teams are also increasingly using generative AI during the concept phase. This allows them to rapidly create variations of characters, environments, creature designs, and visual moods.
“If you have to create a creature or hero asset for a movie, AI can generate hundreds of concept variations very quickly. Traditionally, such iteration cycles required extensive manual design work and multiple review rounds. AI has compressed those timelines significantly,” said Shajy Thomas, the cofounder and CTO of Astra Studios, a VFX and creative solutions company backed by renowned film production house Hombale Films.
Studios are also using AI-generated storyboards, previs sequences and shot breakdowns to communicate visual direction internally between directors, production designers, cinematographers, and VFX teams.
Its impact is also extending deeper into VFX pipelines. Image-to-3D generation models are increasingly being explored for secondary characters, props, environmental assets and background elements that otherwise take a lot of modelling and texturing effort.
At the same time, software ecosystems, including Adobe, Houdini and Foundry, are integrating AI-assisted tooling directly into creative workflows to accelerate repetitive VFX tasks.
However, the catch here is that while generative AI can create impressive videos, it struggles to produce consistent, controllable, and production-ready outputs at film quality. Maintaining character continuity, lighting consistency, camera coherence, and realistic performances across multiple shots still requires substantial human intervention.
This is where startups like NeuralGarage are positioning themselves. Its VisualDub technology helps filmmakers correct dialogue and improve lip-syncing without expensive reshoots. More recently, it launched Drama, an AI expression editor that allows creators to alter facial expressions after footage has already been generated or filmed.
Beyond generative visuals and editing tools, a new category of AI startups is also attempting to build operating systems for film production. London-headquartered Storyvord AI, an AI coproducer platform focused on American and European film markets, is building tools for budgeting, compliance, scheduling, storyboarding and predictive audience analysis.
“The next layer in filmmaking is predictive analysis. AI should be able to tell how likely a film is to perform even before you make it,” said Gaurav Sharma, the founder of Storyvord AI.
AI Is Rewriting The Economics Of Filmmaking
Perhaps the most disruptive aspect of AI filmmaking is economic. Historically, ambitious fantasy films, war sequences, or large-scale mythological worlds were reserved for studios capable of deploying enormous budgets.
AI is collapsing those barriers. Mythological productions that traditionally required hundreds of crores could now be created at a fraction of the cost using AI-assisted pipelines.
“When we are showing Hastinapur or the battle of Kurukshetra, we are no longer bound by limitations of thought and vision,” said Subramaniam of Collective Artists Network.
Along with creative leverage, the more crucial shift is that the technology has dramatically lowered the cost of experimentation and risk-taking. Independent creators, regional storytellers, and smaller studios may now attempt projects that were previously impossible due to financial constraints. High-concept science fiction, mythology, fantasy worlds and stylised cinematic universes are no longer exclusive to deep-pocketed production houses.
This is already visible in short-form content ecosystems, where AI-generated microdramas and creator-led cinematic experiments are rapidly mushrooming across digital platforms.
Industry Still Needs Human Filmmakers
Despite the rapid progress in generative video models, AI filmmaking remains far from a one-click process. Most AI-native studios are operating through hybrid pipelines where traditional filmmaking expertise is deeply embedded in the workflow.
Studio Blo’s teams, for instance, still include cinematographers, VFX artists, illustrators, production designers, editors, and actors working alongside AI systems.
“The biggest expense in an AI film is still people,” said Studio Blo’s cofounder and CEO, Dipankar Mukherjee.
While AI models can generate visually striking scenes, but preserving expressions, matching lighting, maintaining continuity and ensuring cinematic coherence still require extensive human intervention.
The industry appears to be moving toward AI-assisted production environments where human creators continue driving intent, emotion, storytelling, and cinematic judgment while AI expands production scale and flexibility.
For younger independent filmmakers, AI is increasingly becoming less of a replacement tool and more of a creative collaborator.
Currently, most productions are heavily reliant on traditional shoots with selective AI augmentation layered across pre-production, VFX, dubbing, or editing. However, streaming platforms are warming up to AI-generated formats. AI-native studios are emerging as standalone production entities. Creators are building proprietary IP engines, synthetic celebrity systems and orchestration platforms for entertainment workflows.
Amid all this, as the industry tries to make sense of the grammar of AI cinema, neither cameras nor filmmakers will disappear anytime soon. This simply means that human creativity will remain indispensable even in the age of AI.
The post How AI Is Taking Over The Director’s Chair appeared first on Inc42 Media.
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