Summary of Key Points
By 2026, AI will have fully integrated into the entire film and television production process (planning, filming, post-production, etc.). From Netflix's 300 works that utilize AI to China's iQiyi's compliant AI feature films, the technical tools and workflows are mature enough. However, the core issue in the industry is no longer whether AI can produce films, but rather the fact that despite having all the necessary tools at hand, there is a lack of high-quality content that truly resonates with audiences. People are still preoccupied with technical details rather than using AI to create compelling stories.
Detailed Analysis
1. AI has long entered the film and television industry, so why don't we see more impressive works?
AI in film and television is not a "future concept" but a reality that is already happening. Netflix has used generative AI in 300 of its works this year, mainly for post-production purposes; iQiyi has released China's first compliant AI feature film, "Qi Tan: Paper Blade Crossing the Wasteland" (60 minutes); Tencent is also working on long AI dramas and films. However, ordinary audiences don't notice these advancements because most AI applications are hidden behind the scenes (such as post-production image editing or special effects generation), or the resulting works are either experimental short films or have weak plots. The problem lies in the misalignment of industry focus: for years, discussions have revolved around whether AI can produce good-quality content (in terms of image quality, length, character consistency), and with each technological advancement, the bar for what is considered "acceptable" has moved lower. By 2026, the question should no longer be whether AI can enter the industry, but rather why no one is using it to tell meaningful stories.
2. No matter how advanced the workflows are, they cannot replace the creativity of creators
There are countless AI tools available today: overseas platforms like Runway and Pika, and domestic ones like Keling and纳德Pro, covering everything from script generation to storyboarding and editing. Platforms are promoting "AI workflows" (such as Tencent WorkRally, which combines script analysis and asset generation into a single system), claiming that one computer can handle the entire production process.
However, a workflow is just a set of tools, not creative content itself. Just because you have all the kitchen appliances doesn't mean you can make a Michelin-starred meal—workflows solve the problem of how to produce content more quickly, but they don't answer the question of why that content should be made in the first place. For example, while systems can automatically analyze scripts, it's still up to humans to decide whether a script is worth filming; they can generate hundreds of character designs, but it's the director who decides which characters will connect with the audience; and they can create storyboards from text, but the director decides whether the camera should be close to the characters or pull back. Even traditional production teams with established workflows haven't produced great films just by using new editing software. The same applies to AI in film and television: tools are helpful, but creativity and judgment remain crucial.
3. No single stunning shot is enough to make a good movie
AI excels at creating impressive individual shots—scenes like cities rising from the clouds or ancient armies marching through deserts look incredible on their own. However, a movie is more than just a collection of shots; it requires coherent character development, a logical plot, and gradually building up emotional tension. For instance, in Neil Blomkamp's 13-minute short film "Nightborne," AI was used for photography and set design, but the director still had the final say on the core creative elements (story direction and character motivations). Conversely, if you just pile together a bunch of beautiful shots without a coherent narrative, audiences will lose interest after a few minutes. The lower the threshold for generating content, the more valuable becomes the ability to select and organize these elements effectively.
4. Stop showing off technology; let the content speak for itself
Nolan's new film "Odyssey" serves as a lesson for AI in film and television. In an era of widespread digital photography, he chose to shoot the entire film with IMAX film cameras (available in only 41 theaters worldwide). This isn't about which medium is better, but whether the content can provide a compelling experience for the audience. Audiences are willing to seek out the film's film version because of Nolan's reputation, which has brought the nearly obsolete film format back into prominence. The same goes for AI in film and television: audiences won't be impressed just because something was made with AI; they care about whether the story is engaging and the characters are compelling. The evaluation criteria should change from asking what tools were used to focusing on the quality of the final product and whether it captures the audience's attention. Technical experiments are welcome, but they shouldn't always serve as an excuse for subpar content.
By 2026, with powerful models and a wide range of workflows available, the industry should stop proving that AI can produce films and start using it to create good ones. Just as digital technology replaced film because it better served the needs of content creation, AI should become a tool in service of storytelling, not a selling point for the final product.
Conclusion
The next step for AI in film and television is not to develop more tools but to enable creators to use them to tell stories that audiences want to see. Tools should support the content, and technology should serve the expression of ideas—this is what truly defines the essence of film and television.
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