If you have used AI video tools, you may have noticed an interesting trend: generating a visually impressive video is becoming easier, but turning it into a commercial-ready production is still far from simple. What happens when a subtitle is wrong? What if product data needs to be updated? If a brand logo appears in the wrong place, does the entire video have to be generated again?
These issues may be acceptable for creative content on social media. But for product explainers, brand marketing and commercial advertising, videos need to be more than visually appealing. They must be accurate, visually consistent and easy to revise.
This is where Fotor Agent comes in. Launched in August, the tool builds on Fotorโs background in photo editing and visual design, extending its AI capabilities to the entire video production workflow. Rather than simply generating clips, it aims to help users turn text prompts into finished videos, from content planning to final delivery.
Users start by describing the video they want through text prompts. Fotor Agent then helps organize the production process, bringing together visual assets, subtitles, audio and animations in a single project. The video can then be reviewed and refined on a multitrack timeline, where individual elements can be edited without requiring the entire video to be regenerated.
Turning prompts into editable video projects
In an interview, Jackson Zhang, COO of Fotor, said Fotor Agent plans content based on users’ creative goals and coordinates tasks such as asset generation, graphic rendering, subtitles, audio and animation. It then brings these elements together in a unified video project.
For a product explainer, for example, the system must do more than generate visuals. It needs to organize shots, text, charts, voiceovers and animations into a coherent sequence. For commercial content, how well these elements work together can matter more than how impressive an individual shot looks.
One of Fotor Agent’s key features is its ability to produce video projects that retain their timeline and internal structure. Users can independently edit text, data, logos, visual assets and animations without regenerating the entire video every time a small change is needed. They can also review and fine-tune details directly on a multitrack timeline.
The workflow behind better AI videos
As foundation models continue to improve, products using similar third-party models may be able to generate visuals of comparable quality. For AI creation platforms, building a competitive advantage on top of these models has become an increasingly important challenge.
Zhang said Fotor combines third-party AI models with its own image-processing algorithms and editing tools. While third-party models handle most tasks, Fotor uses its proprietary technology in selected scenarios.
He believes the more difficult capabilities to replicate lie in the entire creative workflow, including autonomous planning, motion graphics production, precise editing and the quality and effectiveness of the final output.
This also explains why Fotor Agent focuses on motion graphics (MG) and editable video projects. Product promotions, data visualizations and educational videos often require charts, text, animations and brand elements to work together. Users need AI to produce content quickly, but they also need precise control over individual elements.
However, integrating the workflow does not mean every challenge has been solved. Maintaining consistency across assets generated by different models, interpreting complex instructions accurately and ensuring that local edits do not disrupt other parts of a video remain ongoing challenges for AI video tools.
The commercialization test is just beginning
Fotor Agent targets content creators, e-commerce merchants and brand marketing teams. These users have clear efficiency needs, but they also demand accuracy and production quality.
Zhang said Fotor Agent has already generated paid revenue since launch, although the product remains in the early stages of promotion and optimization. Fotor has more than 12 million monthly active users across over 200 countries and regions, according to the company.
These figures reflect Fotor’s overall user base, however, and should not be taken as indicators of Fotor Agent’s own user growth or retention.
To attract overseas users, Fotor relies on channels including SEO, influencer marketing, community engagement and paid advertising. The company also engages directly with local creators and brands to understand the visual styles and content production needs of different markets.
Zhang noted that localization for video products involves more than language. It also requires an understanding of visual styles, communication preferences and real-world use cases.
Fotor Agent must now demonstrate that its integrated production workflow can translate into efficiency gains that users are willing to pay for, while building lasting usage habits.
AI streamlines production, while humans retain creative judgement
Zhang believes AI Agents will take on more content planning, asset organization and production tasks over the next one to two years, which will enable small teams to produce videos that once required collaboration among multiple specialists. However, creators will still need to decide what their content should communicate and judge whether the final result meets their goals.
For Fotor, the next priority is to improve the accuracy and convenience of editing. In commercial videos, text, data and brand elements must be correct. How easily these details can be revised after generation will directly affect whether the product can achieve widespread adoption.
The next phase of AI video competition may not simply be about which tool can generate the most realistic visuals. It may instead be about which tool can turn creative ideas into deliverable content more reliably and efficiently.
Video creation is only one part of the process. A truly useful AI Agent should free creators from tedious production work while preserving their control over the final result.
