The Flagship Cases

The clearest evidence that India’s AI production bet is real — and not merely a PR exercise — is the scale and variety of the projects now in market or production.

JioStar: Mahabharat as a Proof of Concept

The most watched and most discussed AI production in India is JioStar’s Mahabharat: Ek Dharmayudh, a 100-episode retelling of the Kurukshetra War launched in October 2025. The series, produced through Collective Artists Network’s Galleri5 cinematic AI lab in Bengaluru, drew 6.5 million views on launch day — performance 2.1 times the platform’s average, according to Stephan Bugaj, JioStar’s Senior Vice President of GenAI Content and Technology.

JioStar has been explicit that this was never conceived as a one-off experiment. The platform is now planning a full slate — including the AI-generated series Makaraj, a feature film on Hanuman, and a set of micro-dramas — entirely written, animated, voiced, and edited by AI. To execute the expansion, JioStar is recruiting approximately 80 AI engineers and specialists. The company’s posture is that of a studio restructuring its content factory around a new production method, not an innovation team running a pilot.

The audience reception, however, is more complicated. Mahabharat: Ek Dharmayudh holds a 1.4 out of 10 on IMDb, with reviewers criticising lip-sync issues, low-quality sequences, and styling that felt inauthentic to a sacred epic. JioStar senior executive Alok Jain called the response “a mix of appreciation and healthy debate, which is natural for any ambitious creative leap.” That framing is diplomatically calibrated: 26.5 million total views — logged since October — indicate genuine engagement, even as quality criticism persists.

Abundantia Entertainment: $11M AI Studio, 33% Revenue Target

Vikram Malhotra’s Abundantia Entertainment has made the most explicit capital commitment to AI production of any major Indian house. The company is building a dedicated AI studio with an $11 million investment and has set a target of generating one-third of its total company revenue from AI-assisted content within three years. Abundantia is also preparing to release Chiranjeevi Hanuman – The Eternal — described by Indian media as the country’s first AI-generated theatrical feature film — directed by National Film Award winner Rajesh Mapuskar, who previously worked with Rajkumar Hirani on 3 Idiots and Munnabhai MBBS. That casting — a credentialed mainstream director attached to an AI-native production — is a significant signal of legitimacy.

Eros Media World: Rewriting History

Perhaps the most provocative AI production case in India is Eros Media World’s re-release of the 2013 romantic drama Raanjhanaa — but with an AI-generated alternate ending. In the original, the protagonist Kundan dies after unrequited love. In Eros’s Tamil-language re-release, he opens his eyes to the surprise of his lover. The commercial outcome was genuine: re-release attendance in August 2025 ran 12% above comparable films, according to Reuters. But the artistic and legal fallout was severe. Director Aanand L Rai publicly disassociated himself from the version. Lead actor Dhanush said on X that the AI remake had “stripped the film of its very soul” and set a “deeply concerning precedent for both art and artists.” Eros, citing its copyright ownership under Indian law and Rai’s contractual waiver of moral rights, held its ground. The dispute escalated to the National Company Law Tribunal and generated extensive coverage in Variety — establishing it as India’s first AI filmmaking legal landmark.

Amazon MX Player: Period Reconstruction at Scale

The series Made in India: The Titan Story, streaming on Amazon’s MX Player, demonstrates AI’s application not in full-generation content but in targeted visual effects work: over 100 AI-generated VFX shots were used to recreate 1970s Mumbai. AI artist Prasad Gori, who worked on the project with partners Anurag Tiwari and Sagar Chogale, told CNBC that the volume of AI production work he receives has transformed in the space of eight months — from chasing production firms for work three years ago to fielding 10–15 offers per week now.

The Creativity Question: Where AI Is Working, and Where It Isn’t

The commercial data and the artistic data point in different directions, and both deserve honest accounting.

AI currently performs best in Indian production contexts when it is applied to visually stylised, fantastical, or historical content where authenticity standards are lower, or where AI’s output serves as a reference rather than a final product. Mythology and fantasy genres — which require imagined worlds, divine characters, and non-naturalistic visual language — are a natural fit. Period reconstruction, as with Made in India‘s 1970s Mumbai sequences, leverages AI’s strength in combining archival visual reference with generative synthesis.

The hybrid approach emerging from studios like FirstAI Consultancy — using human performance as input to direct AI character generation — is a more sophisticated response to the current limitations. By capturing actors’ facial expressions via motion-capture or reference footage first, then using AI to render stylised output from that base, studios avoid the problem that has most visibly damaged audience confidence in full AI generation: unconvincing emotion, dead-eye characters, and the uncanny valley in realistic human depictions.

“Using generative AI has really allowed me to change my vocabulary. When you type a prompt and see a physical representation of the words you used — that’s not what I wanted. What words do I need? How do I generate an emotional response? Over three years doing that, my use of language in the creative world has fundamentally changed.”

— John Kilshaw, Framestore · Vitrina LeaderSpeak Epi. 50

The audience reception data is instructive, even if producers are reluctant to foreground it. A 1.4/10 IMDb rating is one of the lowest ever recorded for a major platform production. Criticism concentrated on lip-sync failures and what reviewers described as inauthentic styling. For a series retelling one of Hinduism’s most sacred texts, the cultural stakes of inauthenticity are higher than they would be for, say, a sci-fi thriller. The mythology-AI pairing that looks economically smart has a corresponding cultural risk: audiences who revere the source material are more likely to find AI’s current imprecision in character and expression offensive rather than acceptable.

“AI has made filmmaking simple for small teams who are struggling to find producers or investors.”

— Sudharshan Srinivasan, Executive Producer, Tamil Film Industry

The democratisation argument is where AI’s impact is clearest and least contested. Sudharshan Srinivasan, an executive producer in the Tamil industry who has spent years trying to break in as a director, told CNBC that AI now gives independent creators a viable path to production without the traditional gatekeepers: financing relationships, star access, and distribution networks built over decades. If he cannot find a backer within two years, he plans to produce his feature film via AI and release it directly on a digital platform. That pathway — AI as creative infrastructure for the excluded — is generating a genuine wave of independent content that has no equivalent in any other major film market.

Strategic Implications for the Global Entertainment Industry

The data emerging from India’s AI production experiment carries implications well beyond the subcontinent. Four dynamics are worth tracking closely.

1. India Will Export AI Production Methods Before It Exports AI Content

The workflows, tool stacks, and hybrid human-AI production pipelines being developed in India will likely be adopted by mid-budget studios in Southeast Asia, the Middle East, and Africa before they reach Hollywood. The appetite for localised content in those markets — combined with economics closer to India’s than to the US — makes them natural recipients of India’s emerging AI production playbook. Companies like Vitrina that track production intelligence across these markets are positioned to identify this diffusion early.

That diffusion comes with a displacement risk, however — one that hits India’s own existing service economy first. The roto, tracking, and prep work that built India’s VFX outsourcing industry are precisely the functions AI automates fastest.

“The disciplines where AI is going to impact first are rotoscoping, tracking — the preparation phases. Companies in India who specialised in being a white-label outsourcing operation — that’s a business model they would need to pivot quite rapidly.”

— Neil Hatton, UK Screen Alliance · Vitrina LeaderSpeak Epi. 46

2. The Legal Framework for AI Authorship Will Be Contested — and Consequential

The Eros-Raanjhanaa dispute is India’s first significant AI filmmaking legal case, but it will not be the last. The core question — who owns the right to modify a creative work using AI, and what moral rights the original creator retains — is unsettled in Indian law and in most jurisdictions globally. The outcome of cases like this one will shape the economics of library exploitation for every major studio holding legacy content rights.

3. Audience Tolerance for AI Quality Varies Dramatic by Genre and Market

The 1.4/10 IMDb score for Mahabharat: Ek Dharmayudh versus the 6.5 million Day 1 views is not a contradiction — it reflects a bifurcated audience response that will be characteristic of early AI content. Casual streaming viewers willing to sample a novel format are different from culturally invested audiences who hold sacred epics to high authenticity standards. Studios that match AI production to appropriate genres and audience segments will outperform those that apply AI indiscriminately across their slates.

4. The Democratisation Effect Is Underweighted in Industry Analysis

Most coverage of AI in Indian filmmaking focuses on what JioStar or Abundantia are doing. The more structurally significant shift may be at the independent level — the Srinivasan-type creator who now has a realistic path to producing and distributing a feature film without traditional gatekeepers. If AI removes the financing and infrastructure barriers to entry for independent Indian filmmakers, it could generate a wave of micro-budget, platform-native content in regional languages that increases total content supply in ways that alter platform economics and talent discovery dynamics across the industry.

“AI is slashing production costs to one-fifth of what they used to be for traditional filmmaking in genres such as mythology and fantasy.”

— Rahul Regulapati, Head of AI Studio, Collective Artists Network

The Horizon

India’s AI filmmaking experiment is the most data-rich real-world test the global entertainment industry has. It is running in full public view, generating audience numbers, legal disputes, quality reviews, and capital commitments simultaneously. The picture it is producing is neither the utopian nor the dystopian version of the AI-production narrative that tends to dominate discourse in Western media markets.

What is emerging is something more granular: a production modality that offers genuine and substantial economic advantages, is currently constrained by specific technical limitations (particularly in realistic character expression and lip-sync), performs best in genre contexts where visual stylisation is expected rather than realism demanded, and is rapidly attracting institutional capital and global technology partnerships.

JioStar is hiring 80 AI engineers. Abundantia is building an $11 million studio. Floating Tiger and Studio Blo are winning industry awards. Google and Nvidia are in the room. The experiment has become infrastructure. For the global entertainment industry — studios, streamers, production companies, and technology vendors tracking where production paradigm shifts originate — India is the story to watch in 2026 and beyond.