Summary of the Key Points
This report provides a comprehensive account of the absurd rise and fall of the AI-driven film and television industry, based on the personal experiences of Mr. Huang, an entrepreneur in the cross-industry AI film and television sector. In 2025, with the emergence of large AI video models such as Sora, the entire industry was swept up in the myth that using prompts would enable easy profits and that AI would revolutionize the traditional film and television industry. A large number of entrepreneurs, many of whom had no prior experience in the industry or understanding of technology, jumped into the market and made quick money by taking on low-cost outsourcing projects. However, within less than half a year from the beginning of 2026, the industry plummeted from frenzy to despair. Nearly half of the AI film and television production teams closed down. Essentially, the early entrants mistook the short-term benefits of AI tools for a long-term business model that would guarantee success, resulting in widespread failure.
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Detailed Explanation of the Key Points
1. Why did the entire industry go crazy for the AI film and television trend? How was the myth of "making money with just a few prompts" created?
When AI video technology first emerged in 2025, it seemed like a windfall:
To produce a traditional commercial ad costing 50,000 yuan, one didn't need to rent a venue, hire actors, or arrange lighting and crew. A small team of five or six people could use AI tools to create a video in just a few days, with a cost of only 20,000 yuan and a gross profit margin of 40%-60%. Everyone was blinded by this prospect, thinking that the cost of producing one video was similar to that of producing 1,000 videos, and that the content could be produced indefinitely, leading to endless profits.
The media was also hyping up the potential of AI to transform the film and television industry, and investors flocked to fund projects. All industry forums were discussing AI. Even those from fields like pharmaceuticals or the internet thought they had found a shortcut to financial freedom. They could simply assemble a team and start taking on projects without realizing the potential pitfalls.
2. Why did the dream of quick profits shatter so quickly? Internal and external factors combined to shut down many small businesses?
Early investors like Mr. Huang, having made money, planned to expand their operations by raising funds to buy more hardware, licenses, and content rights, as well as renting office space. However, they soon found themselves trapped:
- Rising costs from upstream providers: In the spring of 2026, the cost of AI computing power on platforms like Alibaba Cloud and Baidu Cloud increased by about 30%. For example, what used to cost 100 yuan to produce a one-minute animated video now cost 200-300 yuan, resulting in a significant loss of profit. Additionally, the quality of AI-generated content was poor, with characters' faces changing, hands having extra fingers, and movements appearing unnatural. Fixing these issues required extensive manual editing, which was hardly more efficient than traditional production methods.
- Competitive pricing from downstream buyers: Hundreds of new studios emerged, competing on price. Customers compared quotes and chose the lowest bidder, squeezing the profits of producers. Platform分成 rates also plummeted, from 100 yuan for 10,000 views to just 5-10 yuan. For a video with 180 million views, producers could only earn 180,000 yuan, not even covering their costs. Platforms stopped providing guaranteed payments and relied solely on performance-based commissions, leaving producers with no guaranteed income without hit videos.
3. Why did these early entrepreneurs end up in a dead-end situation?
These small AI film and television companies found themselves stuck with no clear competitive advantages:
They couldn't compete with traditional studios in terms of quality, as their AI-generated content was poorly crafted and lacked narrative coherence. They also couldn't compete with tech companies, as they lacked the capability to develop their own large models and couldn't afford to maintain top-tier teams. The tools they used (such as Sora and Kailing) had no significant technological barriers, meaning they had no real advantage over their competitors.
Even the low-cost advertising outsourcing market was crowded, and experienced prompt engineers left to work independently, earning more than they did in their companies. With fewer orders and slower revenue, many companies went bankrupt. Some resorted to illegal activities, such as selling adult content overseas, facing serious legal consequences.
4. Who were the winners in this trend? Who didn't suffer losses?
In the end, the only winners were those who focused on different aspects of the industry:
- Companies that developed large AI models and sold computing power: They charged fees for their tools and used computing resources, ensuring a steady income regardless of the performance of the projects.
- Short video and drama platforms: They could purchase low-cost AI-generated content, saving on production costs and using it to enrich their content libraries, thus earning a stable profit.
- Early investors who withdrew before the industry heated up: They made quick money from low-cost outsourcing projects and then withdrew their investments before the industry became overly competitive, securing their profits.
5. Where are the opportunities now that the AI film and television trend has cooled down?
The failure of the AI film and television trend is not due to the technology itself but rather to a misalignment in everyone's approach. The focus was on saving costs through AI, rather than on creating high-quality content that users would want to watch. The industry will now undergo a reshuffle, and only those with resources and the ability to invest in developing large models and optimizing content production processes will survive. The era of easy profits through cheap AI tools is over.