Evaluate whether AIGC assets match brand communication goals
Before launching any AIGC project, the core communication goals must be clear. Brands need to determine whether the content is for increasing brand awareness, showcasing product features, or driving immediate conversion. AIGC excels at handling abstract concepts, surreal visuals, or high-frequency asset production, but may have limitations in scenarios requiring extremely high realism or complex interaction logic. If a project relies on precise product detail display or real human emotional resonance, additional assessment of the credibility threshold of AI generation is needed. Do not view AIGC as a universal solution, but rather position it as a tool for specific visual styles or efficiency optimization.
Prepare a differentiated content asset list
Different channels have completely different content requirements. Brands need to organize a detailed asset list in advance, distinguishing which elements are suitable for long website videos and which for short social media videos. Websites usually require a complete storyline and high-definition quality, while social media emphasizes the hook of the first three seconds and vertical composition. When preparing materials, clear reference images, a list of core selling points, and visual elements that are prohibited should be provided. Without clear instructions, AI-generated content can easily deviate from the brand tone, leading to a surge in later revision costs. Be sure to confirm the copyright clarity of all input materials, and avoid using unauthorized music or image styles as a training basis.
Establish a standardized brand visual constraint library.
To ensure consistency in generated content, the team needs to build a strict visual constraint library. This includes defining the hex codes of the primary color palette, font specifications, and motion graphics style guides. In prompt engineering, these parameters should be solidified as default settings. For characters, facial features, clothing styles, and even micro-expression ranges must be specified. This standardized processing ensures that the same set of AIGC assets maintains brand image consistency when presented across different channels. If the style is disjointed between modules, it will severely weaken the brand's professional feel.
Build a reusable modular workflow.
To achieve multi-platform reuse, the production team should adopt a modular mindset. Split the video into independent visual modules, such as opening effects, product display segments, and character speaking backgrounds. Each module should maintain consistency in resolution and frame rate for flexible recombination later. In the pre-planning phase, determine the primary color palette, font specifications, and motion graphics style guide. This standardized processing ensures that the same set of AIGC assets maintains brand image consistency when presented across different channels. If the style is disjointed between modules, it will severely weaken the brand's professional feel.
Prompt engineering and iteration in the execution phase.
The core of shooting and generation lies in precise prompt engineering. The team needs to establish an internal prompt library to record verified effective instructions. For key shots, it is recommended to generate multiple times and screen the best results, while avoiding reliance on a single output. Pay attention to controlling randomness by fixing seed values or using reference images to maintain character and scene consistency. If errors are found in AI-generated body structures or text, intervene and correct them promptly, rather than hoping for post-production fixes. The level of detail in this phase directly determines the usability rate of the final cut.
Key technical integration points for post-production compositing.
AIGC-generated segments usually require post-production compositing to meet commercial standards. Editors need to handle audio sync, color matching, and transition effects. Since the lighting and shadows of AI-generated footage may differ from live-action assets, the color grading stage is crucial. Sound design can inject life into static or low-motion AI visuals. Subtitles must not only be accurate but also comply with accessibility reading standards across various platforms. If these details are ignored, the final cut will appear rough and lack texture, failing to meet delivery requirements.
Establish a strict acceptance checklist.
Before delivery, the team should conduct item-by-item acceptance based on the following standards. First, check visual consistency to ensure seamless transitions in color and style between different segments. Second, verify technical specifications, including whether resolution, bitrate, and format meet publishing platform requirements. Third, review content accuracy, especially regarding product names, data, and legal statements. Finally, test multi-device playback performance by previewing on mobile phones, tablets, and desktop devices to ensure compatibility. Failure to meet any of these criteria may result in delivery failure or damage to the brand image.
Copyright and Compliance Review
When using AIGC content, copyright issues are a risk that cannot be ignored. Brands need to confirm the license agreements of the AI tools used and clarify the commercial rights for the generated content. If it involves imitating the style of a specific artist or using protected character images, it may lead to legal disputes. It is recommended to clearly define copyright ownership and responsibility division in the contract. In addition, attention must be paid to the labeling requirements for AI-generated content on various platforms, such as honestly disclosing the use of AI technology, to comply with the latest regulatory trends.
Identifying Unsuitable Scenarios and Alternatives
Typically, not all projects are suitable for AIGC. If a brand's core value is built on extreme realism or unique craftsmanship, the generic aesthetics generated by AI may dilute the brand's personality. For projects requiring highly customized interactive experiences or real-time data feedback, traditional production or hybrid workflows may be more reliable. When the budget is extremely tight and time is pressing, although AIGC can produce videos quickly, the lack of fine polishing may instead increase communication costs. In this case, simplifying the creative scope or using templated videos may be a more practical choice.
Next Step Recommendations
It is recommended that brands start with small-scale pilots, such as producing a set of social media short videos or website background animations, to test the stability and effectiveness of the AIGC workflow. Adjust the prompt library and acceptance standards based on the pilot results, and then gradually expand the scope of application. At the same time, establish an internal training mechanism to improve team members' ability to master AI tools. Regularly review asset reuse and optimize the content structure. Keep an eye on the development of new technologies and introduce more efficient tools when appropriate. Through step-by-step practice, gradually build a brand-specific AIGC content asset system.
If you are preparing an AIGC content asset project, you can first organize the brief, reference visuals, product or corporate materials, delivery platforms, and copyright scope, then checkAIGC Video Service Pageto move the communication from abstract preferences to executable production boundaries.
