Artificial intelligence is changing how movies and series get made, but the biggest players in production are drawing a clear line: AI should support artists, not replace them. At Netflix’s Creative Asia event during the Busan International Film Festival, executives and filmmakers shared a grounded view of AI in film production—one focused on efficiency, creative flexibility, and cost control, while acknowledging the technology still has major limits.
The discussion brought together Weta FX Chief Technology Officer Kimball Thurston, Netflix APAC Senior Director of Production Sung Q Lee, and Korean filmmaker Kang Yun-sung. Their message was strikingly consistent: AI in film production is already useful in specific stages of the workflow, but it is not yet a substitute for human judgment, emotional storytelling, or performer-driven scenes.
How AI in Film Production Is Being Used Right Now
Rather than relying on fully generated scenes, studios are applying AI in film production to targeted tasks that improve speed and reduce friction behind the scenes. According to the panel, current applications are practical rather than flashy.
- Image clean-up and post-production polishing
- Generating motion for crowd scenes
- Pre-visualization before principal photography
- Editorial assistance and workflow acceleration
- Visual effects support for complex sequences
This use of AI in film production reflects a broader industry trend: filmmakers want more iterations and more options, not necessarily machine-made final images. That means AI can help a director test alternate sunsets, battle staging, or environmental details without immediately committing major budget and labor.
Netflix’s team emphasized that AI is reviewed through internal guidelines and is not being deployed simply to appear innovative. The stated priority is improving the viewer experience, while preserving the creative process that audiences ultimately respond to.
The Benefits: Faster Workflows, Lower Costs, Bigger Creative Ambitions
For producers and directors, the appeal of AI in film production is easy to understand. It can reduce turnaround times, cut costs, and make visually ambitious storytelling possible at budgets that previously would not support it.
Kang Yun-sung, whose work includes South Korea’s first feature-length AI-assisted film, argued that the technology is especially meaningful for genre filmmaking. Historically, action-heavy or effects-driven projects in many markets were constrained by budget ceilings. AI tools can help bridge that gap by enabling scenes that would otherwise be too expensive or too slow to shoot.
That impact is especially relevant for Netflix’s upcoming Korean-language thriller Gulf Of Aden, which uses AI-assisted workflows to recreate war-torn settings, pirate attacks, and hijacked ships. Kang said the production achieved savings in the 30% to 40% range—not only because of lower CGI demands, but because the overall shoot and post-production process became more streamlined.
Why those savings matter
When AI in film production works well, the benefits go beyond the balance sheet:
- More room for experimentation during development
- Greater access to ambitious visual storytelling
- Shorter production timelines
- Improved ability to scale action and world-building
- Potential support for regional industries competing globally
For fast-growing entertainment hubs like South Korea, these advantages may prove especially valuable as studios seek to produce globally competitive content with tighter production windows.
The Limits of AI in Film Production
Despite the optimism, the panelists were careful not to oversell the technology. Thurston noted that some technical issues are improving, including the ability to output in 4K, but other problems remain unresolved.
One major concern is color fidelity. AI systems trained on limited sets of visual material may struggle to reproduce accurate color volume and nuanced tones. In practical terms, that can mean a shot does not deliver the exact visual texture a filmmaker intended. For high-end production, where image consistency matters across cameras, VFX, grading, and display formats, that is not a small problem.
Another challenge is usability. Current AI tools often rely on text prompting, which may not be the most natural interface for visual artists. A cinematographer, concept artist, or VFX supervisor typically thinks in images, motion, lighting, and reference frames—not in prompt-engineering language. Better creative interfaces could be one of the most important next steps for AI in film production.
The human factor still matters most
All three speakers agreed on perhaps the most important point: AI still cannot convincingly replace human performance. It may help construct battle scenes or expand environments, but emotional truth remains tied to actors, directors, editors, and craftspeople.
Kang directly questioned whether AI can yet communicate real human feeling to an audience. For now, the answer appears to be no. That reinforces a growing industry consensus that AI in film production is strongest as an assistive tool, not as a replacement for the people whose work gives stories emotional weight.
Netflix’s Cautious Approach to AI
Netflix appears to be taking a measured position. Sung stressed that the company has strict internal processes around the use of AI and is not racing to adopt it for every task. That stance is significant at a time when entertainment companies face pressure to cut costs while maintaining quality and audience trust.
The company is also framing the conversation around responsible implementation. Questions around sustainability, including the resource demands of AI systems, remain part of the discussion. While AI often dominates headlines, Sung suggested that environmental responsibility in production must be considered within a wider net-zero strategy rather than in isolation.
In other words, AI in film production may be part of the future, but it is only one piece of a much bigger transformation involving workflow design, creative labor, sustainability, and global content competition.
What This Means for the Future of TV and Video
The most realistic takeaway is that AI in film production is entering a practical phase. The conversation is moving away from hype and toward deployment: where the tools genuinely save time, where they fail, and where human expertise remains irreplaceable.
For viewers, that may translate into more ambitious worlds, faster post-production, and better use of budgets. For creators, it means learning how to work alongside AI without allowing it to flatten artistry or standardize visual storytelling.
Studios that succeed will likely be the ones that treat AI as an enhancement layer—valuable in pre-vis, VFX support, clean-up, and iteration, but always guided by filmmakers who understand tone, emotion, and narrative meaning.
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As this latest industry discussion made clear, AI in film production is neither a magic fix nor an existential replacement for filmmakers. It is a developing set of tools with real advantages, real flaws, and real potential when used thoughtfully. The studios that get the balance right will not be the ones chasing automation at any cost—they will be the ones using technology to widen creative possibilities while keeping human storytelling at the center.
