How to Define Priorities for Live-Action vs. Generated Content During Project Initiation
When launching an AIGC commercial project, the primary task is to categorize shots based on brand asset security and visual credibility. Marketing leads must organize core teams to break down scripts shot by shot, dividing visuals into four levels: core asset display, emotional atmosphere creation, narrative transitions, and pure conceptual expression. Shots involving product appearance details, brand logos, specific material textures, and key function demonstrations must typically be included in the live-action filming list. This is because current generative models still carry uncontrollable hallucination risks when handling precise geometric structures and fixed text symbols; once product proportions are distorted or logos deform, brand professionalism is directly compromised.
For background environments, abstract concept visualization, surreal transitions, and large-scale crowd scenes, prioritize assessing the feasibility of AIGC generation. The criterion lies in whether the shot carries visual information requiring legal rights confirmation. If the image serves only emotional rendering and contains no commercial elements identifiable as specific physical objects, generative imagery can significantly reduce set construction and personnel scheduling costs. At this stage, the production team must output two comparison tables: one marking mandatory indicators for live-action filming, and another listing flexible spaces suitable for AI generation, noting the risk assessment basis for each decision to avoid rework caused by cognitive misalignment later.
Physical and Digital Materials Brands Must Prepare in Advance
The efficient operation of AIGC workflows highly depends on the completeness of preliminary materials. Brands cannot merely provide a text script or a few inspiration images but should prepare a structured asset package. This includes high-precision 3D models of products or multi-angle high-definition live-action footage, color values and font specifications from the brand visual identity manual, previously approved official image libraries, and a dedicated list of negative prompts for the current project. These materials are the cornerstone for training or constraining generative models; missing any item may cause AI outputs to deviate from brand tonality.
Particular attention must be paid to the level of detail required for reference images. Vague style descriptions cannot guide precise generation; brands should provide specific frame-level references including lighting direction, composition ratios, color temperature tendencies, and depth-of-field relationships. If the project involves compositing real actors with AI backgrounds, confirm in advance whether actor portrait authorization covers secondary creation of generative content. Insufficient material preparation is the main cause of AIGC commercials falling into infinite revision loops. It is recommended to establish a material acceptance checkpoint before formal production, with the production team confirming asset usability in writing before entering the production phase.
Technical Interfaces Reserved for Post-Production Generation During Filming Execution
When certain shots are determined to use a hybrid of live-action and AIGC production, on-set filming is no longer an isolated step but the data collection end of the entire generative workflow. The Director of Photography must consider lighting matching for post-production compositing during lighting setup, recording main light direction, color temperature values, and ambient light reflection characteristics, using gray spheres and color cards as physical benchmarks for lighting restoration if necessary. Camera movement must also adapt to the temporal consistency capabilities of generative models; overly complex handheld shaking or non-standard focal length movements may exceed the stable processing range of current AI video interpolation algorithms, causing background flickering or object drift.
On-site personnel should also be assigned to collect auxiliary data for generation control. For example, simultaneously record HDR panoramas during empty shot filming for environment map generation, or take multi-angle static photos during actor performance breaks for character consistency anchoring. Sound engineers must separately record clean ambient noise and specific sound effect materials, as AI-generated audio-visuals often lack the acoustic characteristics of real spaces, requiring field recordings for sound field reconstruction in post-production. All technical parameters and auxiliary materials must be detailed in daily logs to form traceable production records; otherwise, post-production compositing will face a dilemma of having no basis to rely on.
Quality Control Nodes for Human-Machine Collaboration in Post-Production
Post-production for AIGC commercials focuses on an iterative process of repeated verification and correction. Editors must embed low-resolution placeholder versions of generated shots during the rough cut phase to verify narrative rhythm and information transmission efficiency, avoiding situations where duration or content mismatches are discovered only after high-resolution rendering is complete. The color grading phase must establish a unified color management workflow to ensure live-action footage and AI-generated images reside in the same color space, preventing skin tone banding or environmental color casts after compositing.
To address the uncertainty of generated content, teams should implement a multi-level review mechanism. Initial generation results are checked by the Art Director for style consistency, the second version is confirmed by the brand for core information accuracy, and the final version is reviewed by legal or compliance personnel for potential infringement or misleading visual implications. Each feedback instance should include specific timecodes and problem descriptions rather than vague feelings of incorrectness. For shots that fail to meet requirements after multiple generations, a clear downgrade plan must exist, such as switching to traditional CGI production or adjusting storyboard designs, to prevent the project from consuming budget and schedule on a single technical bottleneck.
Differentiated Verification Checklist for Delivery Acceptance
Acceptance standards for AIGC commercials should differ from pure live-action projects, adding special inspection items targeting generative characteristics. Beyond conventional checks for image quality, audio quality, subtitles, and format compliance, frame-by-frame verification is required to ensure product forms do not deform during motion, brand logos remain clearly legible throughout, human limb movements comply with ergonomic logic, and background elements contain no physically impossible errors. These flaws are difficult to detect in static images but severely undermine viewer trust during continuous playback.
Copyright and compliance constitute another key acceptance dimension. Deliverables must include authorization documents for models and materials used in generated content, confirming commercial license coverage for target distribution platforms and regions. If the project involves generative reproduction of public figures or protected IP, corresponding written authorization chains must be provided. Acceptance documentation should clearly distinguish which frames are live-action, which are AI-generated, and which are hybrid productions, facilitating subsequent audits and re-creation. Products failing any of the above checks should not be considered qualified deliveries, even if their visual effects appear exquisite.
Identifying High-Risk Scenarios Unsuitable for AIGC Commercials
Although generative imagery expands creative boundaries, forcing AIGC usage in certain scenarios increases risks and costs. Fields with strict authenticity requirements, such as high-precision industrial product displays, medical device operation demonstrations, and food safety-related visuals, should currently rely primarily on live-action filming or certified traditional CGI. Such content has extremely low tolerance for error; AI randomness may be interpreted as false advertising, triggering regulatory risks or consumer lawsuits. Additionally, when project cycles are extremely short and brands cannot respond promptly to multiple rounds of feedback, deeply customized AIGC workflows are unsuitable, as generative productionqian qi debugging and mid-term iteration often consume more time than linear live-action filming.
Topics involving sensitive cultural symbols, political issues, or images of minors also require caution. Biases in generative model training data may inadvertently produce offensive content, which manual screening cannot cover one hundred percent. If brands have zero-tolerance requirements for content safety, or if target markets mandate explicit labeling of AI-generated content that would significantly impact dissemination effectiveness, the technical approach should be re-evaluated. Identifying these boundaries ensures technology application always serves long-term brand interests rather than short-term gimmicks.
Pragmatic Next Steps for Project Advancement
After completing the above assessments, it is recommended that brands and production teams hold a technical alignment meeting to solidify shot classification results, material lists, filming interface specifications, and acceptance standards into a project charter. Do not rush into full-scale production; instead, select one or two representative shots for prototype testing to verify workflow feasibility and quality ceilings. Test results should serve as the basis for adjusting budget allocation and schedule plans rather than being directly applied to the entire film. ONCE’s publicly available AIGC commercial and AI product video services can serve as one collaboration option for such tests, but specific solutions must still be customized based on actual project materials. Maintaining a clear awareness of technical limitations guarantees more robust implementation of brand content than pursuing frontier labels.
If you are preparing an AIGC commercial project, start by organizing your brief, reference images, product or corporate materials, delivery platforms, and copyright scope, then view theAIGC Video Services Page, to ground communication from abstract preferences into executable production boundaries.
