Although artificial intelligence-based tools simplify the creation of visually impressive videos, transforming these materials into a finished product for commercial use remains a complex task. Issues arise related to subtitle errors, the need to update product data, or incorrect placement of brand logos, which often requires regenerating the entire video.
These shortcomings may be acceptable for informal social media content, but advertising videos, product explainers, marketing campaigns, and commercial ads require the video to be not only engaging but also accurate, visually consistent, and easily editable.
This is where Fotor Agent comes in. Launched in August, this tool leverages Fotor's expertise in photo editing and visual design, extending its AI capabilities across the entire video production cycle. Instead of simply creating clips, it helps users transform text prompts into finished videos—from content planning to final delivery.
Users begin by describing the desired video through text prompts. Then, Fotor Agent organizes the production process, combining visual elements, subtitles, audio, and animation into a single project. After this, the video can be reviewed and refined on a multi-track timeline, allowing individual components to be edited without needing to regenerate the entire clip.
In an interview, Jackson Zhang, Fotor's Chief Operating Officer, stated that Fotor Agent develops content based on users' creative goals and coordinates tasks such as asset generation, graphic rendering, subtitles, audio, and animation. It then compiles all these elements into a unified video project.
For example, for a product explainer video, the system must do more than just generate images. It needs to structure frames, text, diagrams, voiceovers, and animation into a coherent sequence. When creating commercial content, the quality of interaction between these elements can be more important than the superficial appeal of a single frame.
A key feature of Fotor Agent is its ability to create video projects that maintain their temporal structure and internal organization. Users can make edits to text, data, logos, visual assets, and animation themselves, without being forced to regenerate the entire video for the slightest change. They can also review and fine-tune details directly on the multi-track timeline.
As base models improve, products utilizing similar third-party models can generate visual content of comparable quality. For platforms focused on AI-driven content creation, building a competitive advantage on top of these models has become an increasingly important task.
Zhang noted that Fotor combines third-party AI models with its own image processing algorithms and editing tools. While third-party models handle most of the tasks, Fotor applies its proprietary technologies in specific scenarios.
He believes that the most difficult functions to replicate lie in the entire creative workflow, including autonomous planning, motion graphics production, precise editing, and the quality and effectiveness of the final product. This also explains Fotor Agent's focus on motion graphics (MG) and editable video projects, as product advertisements, data visualizations, and educational videos often require the collaboration of diagrams, text, animation, and branding elements. Users need AI for fast content creation, but they also need precise control over individual elements.
Nevertheless, workflow integration does not mean all problems are solved. Maintaining consistency among assets generated by different models, accurately interpreting complex instructions, and ensuring that local changes do not disrupt other parts of the video remain current challenges for AI video tools.
Fotor Agent targets content creators, e-commerce sellers, and branding teams. These users have clear needs for efficiency, but they also demand accuracy and high production quality.
Zhang reported that Fotor Agent has already generated revenue from paid services since its launch, although the product is still in the early stages of promotion and optimization. According to the company, Fotor has over 12 million monthly active users in more than 200 countries and regions.
These figures reflect Fotor's overall user base and should not be used as an indicator of growth or retention specifically for Fotor Agent. To attract international users, Fotor utilizes channels such as SEO, influencer marketing, community engagement, and paid advertising. The company also engages directly with local creators and brands to understand visual styles and content production needs in different markets.
Zhang emphasized that localization for video products involves more than just language; it also requires understanding visual styles, communication preferences, and real-world use cases. Fotor Agent must now demonstrate that its integrated production workflow can lead to increased efficiency that users are willing to pay for, while simultaneously forming sustainable usage habits.
AI optimizes production, while humans retain creative judgment. Zhang believes that within the next one to two years, AI agents will take on more tasks related to content planning, asset organization, and production, enabling small teams to create videos that previously required the collaboration of several specialists. However, creators will still need to define what their content should convey and assess whether the final result meets their goals.
For Fotor, the next priority is improving accuracy and editability. In commercial videos, text, data, and brand elements must be correct. The ease of making changes to these details after generation will directly impact the product's widespread adoption. The next phase of competition in AI video may not be about which tool can generate the most realistic images, but which tool can more reliably and effectively transform creative ideas into finished content.
