Indian Filmmakers Adopt Generative AI at Scale

Filmmakers and distributors across India are deploying generative AI across multiple production stages. Reporting by CNBC says JioStar, a joint venture between Reliance and Walt Disney, produced a 100-episode series called "Mahabharat: Ek Dharmayudh" using generative AI, and that the series drew 6.5 million views on its launch day and performed about 2.1 times the platform average, Stephan Bugaj, JioStar's Senior Vice President of GenAI Content and Technology, told CNBC by email. Reporting by The Hollywood Reporter documents that Eros International released an AI-altered version of the 2013 film "Raanjhanaa" with a synthetic alternate ending, prompting public objections from director Aanand L. Rai and actor Dhanush. Reporting by Reuters shows studios and production houses, including talent agency initiatives in Bengaluru, are using AI for synthetic characters, dubbing into multiple languages and re-editing older titles.

Editorial analysis - technical context: Sources name a range of creative and production tools in current use, including visual-generation and art tools such as Midjourney and Adobe Firefly, and platform tools cited by CNBC like Seedance, Minimax and Google Studio. Editorial analysis - technical context: Practitioners should note the workflows described in coverage emphasize three technical vectors: synthetic visual content generation, automated dubbing and voice conversion for multilingual releases, and generative-assist drafting for scripting and story outlines (The Streaming Lab reports use of ChatGPT by director Shekhar Kapur for draft scripting).

Editorial analysis: Reporting by Reuters and The Economic Times frames India as an accelerated adoption environment because union constraints that slow AI deployment in Hollywood are weaker in India, and because streaming-driven demand and tighter budgets are pushing studios toward efficiency gains. Editorial analysis: This creates a large, observable dataset of production patterns and audience responses that can inform tooling priorities for ML engineers and product teams building content-production stacks.

What sources report: Reuters cites industry data that the number of moviegoers in India fell to 832 million in 2025 from 1.03 billion in 2019, per Ormax Media, a trend that sources link to streaming growth and pressure on theatrical economics. What sources report: The Economic Times and Reuters describe that AI-assisted recuts and re-releases can produce significant box-office bumps; a Reuters-linked investigation reported 35% of available tickets sold for one AI-modified Tamil re-release, above the reported occupancy average. What sources report: The Economic Times says Eros is reportedly reviewing its 3,000-title catalogue for potential AI-assisted adaptations.

Editorial analysis: Observers should track five indicators:

• •catalogue re-release volume and revenue lift per title as measured in box-office and streaming metrics
• •legal or contractual disputes over altered creative content and rights, as in the Eros case reported by The Hollywood Reporter
• •adoption of automated multilingual dubbing pipelines and their impact on localization engineering
• •vendor consolidation around end-to-end creative stacks (visual generation, voice cloning, editing automation)
• •audience sentiment metrics distinguishing novelty-driven spikes from sustainable engagement

Editorial analysis: Engineers and product teams building media pipelines will encounter practical priorities visible in reporting: robust provenance and rights metadata, scalable speech-to-speech and lip-sync models for multilingual releases, quality-control tooling to catch semantic or continuity errors in synthetic scenes, and instrumentation to measure whether AI-driven variations materially change engagement metrics versus cost. Editorial analysis: Legal and attribution tooling will be increasingly important because coverage shows creators and stars publicly contest synthetic alterations, raising downstream risk for distribution platforms.

Reporting across CNBC, Reuters, The Hollywood Reporter and industry outlets documents that India is a large-scale testing ground for generative AI in filmmaking, producing measurable audience outcomes and public controversies that will matter to engineers, product managers and legal teams working on media-focused ML systems.