AI-driven short films and even full-fledged content verticals to back both long-form and theatrical-focused AI projects, being announced by top Bollywood names such as Ajay Devgn, could help bolster their revenues with minimal investments, say experts.
With titles costing between ₹50 lakh and ₹15 crore, depending on scale, there is a significant interest from brands and sponsors looking to collaborate with long-term IP (intellectual property).
That said, while demand for AI content is growing, monetization is still evolving. Challenges include inconsistent revenue due to fluctuating ad rates, limited premium value for certain formats, and a perceived quality gap in areas such as realism and emotional depth. Additionally, brands remain cautious in adopting AI-led content, with concerns about copyright, authenticity and ethical use continuing to shape the ecosystem.
“A short AI film today can cost anywhere between ₹5-50 lakh, depending on how ambitious you go, or how much detailing the project requires, and a full-length project can still run into a few crores because consistency is expensive. People assume AI is typing a few prompts, and everything’s ready, but that’s not how AI films work. What people miss is that AI reduces shooting costs, but it increases iteration,” said Danish Devgn, founder and chief executive, Lens Vault Studios.
The company Ajay Devgn is chairman of has just announced an AI-driven short film titled Happy Birthday Joshi. Devgn added that relying solely on YouTube ad revenue doesn’t help AI films attract much. “The CPMs (the cost an advertiser pays for one thousand views or impressions of an advertisement) in India are too low for premium storytelling. Even with millions of views, the revenue is decent, but not transformative,” he added.
Revenue streams
There are five real revenue streams for production houses, according to experts.
Anushree Jain, founder of SocialTAG, an influence intelligence consultancy, said ad revenue on YouTube AI content in education and lifestyle earns strong rates, while brand deals with lower production costs mean faster, cheaper branded content at scale.
“OTT is a licensing niche and regional AI series that traditional budgets could never justify, and there is also a catalogue revival that includes dubbing old films into new languages, recutting endings, and re-releasing classics. Many are also selling AI production as a service, making content for brands as a new business line,” Jain added.
There isn’t a fundamentally new revenue stream that AI has unlocked, according to Kajol Bheda, founder of Scribbld, a digital marketing agency. “It’s still brand integrations, platform monetization, IP and licensing, and short-form distribution. What AI changes is how efficiently you can produce content,” Bheda pointed out.
Khvafar Vakharia, executive business head and creative executive producer at Equinox Virtual, agreed that many creators and studios are shifting parts of their content slates to these formats to tap into newer, more scalable revenue opportunities.
He said monetization is primarily driven through advertising on platforms like YouTube and other ad-supported streaming services, along with brand collaborations, sponsored content, and platform licensing deals with OTT platforms. IP-led monetization and repeatable content formats are also emerging as sustainable revenue avenues.
“For traditional studios, the real upside lies in margin expansion and faster content cycles, which could lift revenues by up to 20% over time. However, challenges around discoverability, platform dependence, audience trust, and evolving copyright frameworks continue to constrain scale," said Rajesh Sethi, partner and leader-media, entertainment and sports, PwC India.
"In the near term, AI is best viewed as an efficiency and scale lever rather than a standalone content business,” he added.
Limitations
Pointing out that the limits are clear and the technology does not guarantee outcomes, Jayatu Chaudhury, professor-finance and accounting, IMI Delhi, said a typical AI short draws between 35% and 60% of its revenue from advertising and premium views, 20% to 40% from sponsorships and brand partnerships, and 10% to 30% from commissioned branded content, with the balance coming from licensing, fan support and commerce.
“The structure is diversified—but no single stream is deep enough to absorb a surge in supply. The imbalance is becoming clear: AI is increasing the number of films that can be made, but not the number that can be meaningfully monetized. Supply is scaling. Attention is not,” Chaudhary pointed out.
For traditional studios, over the next two to three years, the technology could contribute roughly 1% to 5% incremental revenue growth, alongside 5% to 15% margin improvement in segments where production costs fall materially. “A studio that once financed 10 projects a year may now finance 20 or more. Most will still fail. But if each failure costs less, the overall economics improve,” he added.
That said, as far as formats go, micro-dramas have already begun experimenting with AI, while there have been some attempts on the OTT side too. Nitin Burman, chief revenue officer, Balaji Telefilms, said that until platforms start commissioning full-fledged AI-driven shows, it will be challenging to unlock the full revenue potential of this format. While a significant portion of production work is already supported by AI, fully AI-generated content at 100% is still some distance away, he added.
“Revenue models for such AI-led content remain platform-dependent, with the primary monetization streams comprising subscription revenues, advertising-led income, and brand integrations, reflecting a hybrid and increasingly digital-first distribution ecosystem," said Chandrashekar Mantha, partner and media and entertainment sector leader, Deloitte India.
The shift to AI underscores a structural transformation in content production, where the technology is not only democratizing access but also redefining cost benchmarks, speed, and scalability across the creative ecosystem, he added.