How AI is changing Filmmaking Worldwide

AI is quietly rewriting how movies and web-series get made—start to finish. What once needed many weeks and large teams can now begin with a laptop, a clear script idea, and the right AI tools. Writers test plots with instant feedback. Directors build shot plans from text prompts. Producers estimate time and costs faster. Music, voices, and multiple-language versions can be created the same day. Result: more ideas on screen, faster timelines, and lower budgets—without lowering quality.

The money tells the story too. The global AI in media & entertainment market is estimated at about $26 billion in 2026, and could reach around $100 billion by 2030—a strong sign that AI filmmaking will keep growing quickly.

The toolset filmmakers are using right now

• Google Veo 3.1: a next-gen text-to-video model that makes short high-quality clips with native audio and better control of story and look. It’s available via the Gemini app/API, with “Veo 3.1 Fast” for speed.
• Runway Gen-3: widely used by creators for text-to-video and image-to-video. It focuses on motion quality and prompt control for cinematic outputs.
• OpenAI Sora (incl. newer releases): turns text into highly realistic video and is rolling out with guardrails for safe use.
• Kling (by Kuaishou): can generate up to two-minute videos at 1080p/30fps—useful for longer shots and social content.
• ElevenLabs: popular for lifelike voices, dubbing, and quick multi-language versions—handy for trailers, teasers, and global releases.

Together, these tools compress the early pipeline: ideas → look tests → sample scenes → trailer. Veo 3.1’s upgraded control and audio, for example, helps directors lock character feel and pacing faster, while Gen-3 and Sora offer strong realism for complex shots.

The creator economy angle (YouTube = your studio)

AI means anyone can become a studio. A solo creator can draft a short film on Monday, generate scenes on Tuesday, add voices and music on Wednesday, and publish on YouTube by Friday—then dub it to Hindi, Tamil, or Spanish the same day. Monetization is also simpler now: creators can apply to the YouTube Partner Program with 500 subscribers + 3 public uploads, and either 3,000 watch hours (12 months) or 3 million Shorts views (90 days); full ad-revenue sharing typically unlocks at 1,000 subscribers + 4,000 watch hours (or 10M Shorts views/90 days).

YouTube has also reminded creators that original, authentic work is key; mass-produced or low-effort content (including some AI spam) won’t qualify.

A leading Indian example

Digikore Studios Limited (NSE: DIGIKORE) is one Indian company pushing hard into this future. It has showcased AI-made motion videos and hyper-real commercials that place real products into AI-generated scenes, indicating how brand films and scripted content can be produced faster with strong visual quality.

The company has also communicated an AI-first content strategy and targets producing more than 1,000 minutes of AI-driven content every year as part of its push into AI-native filmmaking and branded content.

What “all-AI” films and episodes could look like

Over the next few years, expect full AI-made episodes: scripts refined by AI, locations and worlds created from prompts, characters generated or performance-captured with consent, dialogue voiced in multiple languages, and music scored to mood—all directed by a small human core team that sets taste, ethics, and final cut. This isn’t theory anymore; major text-to-video tools and voice platforms are already in creators’ hands, and versions improve month by month.

Bottom line

AI won’t replace human vision—it amplifies it. With tools like Veo 3.1, Runway Gen-3, Sora, Kling, and ElevenLabs, filmmakers can test ideas faster, reduce waste, and tell bigger stories on leaner budgets. Indian studios like Digikore are proving this shift at scale, and individual creators can ride the same wave on YouTube. The winners will be those who learn the tools early, respect rights and ethics, and keep the audience at the centre.