Define brand colors and lighting as measurable specifications during the project initiation phase.
Brand color consistency cannot be solved simply by saying 'maintain brand tone.' During AIGC video generation, model color response is unstable; the same prompt may cause color shifts or brightness drift across frames. Brands must include specific color values, gamut ranges, and allowable deviation tolerances in the creative brief during initiation. This includes reference values for primary, secondary, background, and skin tones, plus acceptable color variance for highlights, shadows, and midtones. These metrics must serve as the baseline for generation and color grading, rather than relying on subjective adjustments after delivery.
Lighting consistency also requires advance definition. Specify key light direction, color temperature, shadow hardness, ambient light intensity, and reflection/specular characteristics. Document these parameters in a lighting style guide with reference images or screenshots. The production team should use this document to set generation parameters, plan on-set lighting, or match looks in post-production. If the brand lacks these assets, the production team should proactively provide a lighting style questionnaire, allowing the brand to select preferences from existing visual materials for conversion into technical specifications.
The acceptance criteria require two documents during project initiation: a brand color specification sheet and a lighting style guide. Both must include specific values or reference images, not just adjectives. If the brand cannot provide values, the production team must propose recommendations based on industry color standards for client confirmation. Skipping this step risks making all subsequent frame matching baseless guesswork, leading to high rework costs.
Sufficient color and lighting anchors must be established during filming to support AIGC workflows.
Even if AIGC is the primary output, live-action footage may still serve as reference or input. Color checker and grayscale cards must be placed in-frame during shooting to serve as anchors for correcting color shifts in generated content. The color checker should include primary brand colors, secondary colors, skin tones, and neutral gray, while the grayscale card verifies luminance range. On-set lighting position, color temperature, illuminance, and camera white balance settings must be recorded and synced with the post-production team.
If a project relies entirely on AIGC without live-action shooting, the filming phase becomes an asset collection phase. The production team must gather existing product photos, scene images, and historical ad frames from the brand as style references for the generative model. These assets must be uniformly processed—cropped, color-graded, and annotated with lighting direction—to form a reference atlas. Since the atlas quality directly impacts generation consistency, every image must be labeled with its source and intended use.
Execution steps include creating a pre-shoot lighting plot indicating the position and angle of key, fill, and rim lights. During shooting, recalibrate the color card whenever the scene changes. Export color data and lighting logs on the same day for delivery to the post-production team. Acceptance requires at least one frame containing complete color and grayscale cards under lighting conditions consistent with the final deliverable. For fully AI-generated projects without live action, this phase shifts to compiling a reference atlas, which must equally ensure complete color and lighting information.
Post-production must use layering and node-based controls to manage brand colors and lighting.
AIGC-generated video frames often exhibit color drift and uneven lighting, which cannot be resolved by a single global grading node. The correct approach is layered processing: first perform basic correction per shot, then locally match brand color areas, and finally unify the global lighting atmosphere. Basic correction covers white balance, exposure, and contrast; local matching uses masks or tracking mattes to isolate brand-colored objects; and global lighting adjustments are achieved via curves and glow nodes.
The production team must establish a color management workflow using the same color profile across every step, from importing generated frames and converting color spaces to mastering outputs. Brand color values must be entered into project settings as grading targets. Lighting consistency must be verified using luminance histograms and waveform monitors rather than visual inspection alone. After grading, export a still frame for each shot to compare against the brand color specification sheet and record any deviations.
Specific actions include creating an independent grading node tree for each shot and labeling each node's function. Use keyframes to control lighting variations, such as simulating sunlight movement or flickering lights. Apply a global adjustment layer on the timeline to unify shadows, midtones, and highlights across all shots. Acceptance criteria require that brand color deviation remains within tolerance, lighting direction is consistent, and no abrupt transitions occur. Over-reliance on auto-matching tools risks a mechanical look requiring manual refinement. If stylized lighting (e.g., high contrast or low saturation) is requested, lighting consistency yields to stylistic goals, but brand colors must remain accurate.
During acceptance, verify acceptable tolerances for brand color and lighting deviations on a frame-by-frame basis.
When reviewing AIGC commercials, brands should not rely solely on overall impressions but must inspect brand colors and lighting frame by frame. The production team must provide an acceptance checklist listing reference values, measured values, and deviation values for brand colors in each shot, along with lighting direction descriptions. Brands should review this checklist on standardized monitors, ideally using identical models to prevent color discrepancies. Inspections must focus on key areas such as logos, product appearance, skin tones, and background environments.
Lighting acceptance requires checking shadow direction, highlight placement, and brightness gradation. Inconsistent lighting between shots, such as shadows shifting from left to right, must be flagged as issues. Brands must define acceptable deviation ranges, such as a color difference ΔE under 3 and brightness variance within 5%. These metrics must be confirmed during project initiation and enforced during acceptance. If standards are exceeded, the production team must rework the content until compliance is achieved.
Acceptance procedures include using professional color grading software to read pixel values and generate reports. Frames should be randomly sampled from the timeline, with at least one frame checked every 10 seconds. All output versions, including master, compressed, and social media formats, must be inspected, as compression can affect color. Regarding consequences, if brands identify deviations during acceptance without contractually defined standards, they may be unable to demand free rework. Therefore, acceptance criteria must be included in the contract at project initiation.
Clearly identify scenarios where AIGC is unsuitable to avoid wasting budget.
AIGC video is not suitable for all brand projects. If brand color requires extreme precision, such as for medical devices or luxury goods, AI generation may fail to meet strict color tolerances. If lighting requirements are complex, involving multiple sources, dynamic lighting, or special reflections, AI generation is prone to artifacts. If the project demands extensive live-action interaction, such as actors handling products, AI generation may lack realistic physicality. In these cases, traditional live action or CGI may be more appropriate.
The criterion is that if a brand has extremely low tolerance for color deviation and cannot accept post-production correction, AIGC may be unsuitable. If timelines are extremely tight and the brand provides no color or lighting references, AI generation carries high risk. If budgets are limited but multiple output versions are required, AI generation may increase post-production costs. Production teams must clearly communicate these limitations during the proposal phase and offer alternative solutions.
Specifically, conduct a technical test before project launch to generate sample frames for the brand to evaluate against color and lighting expectations. If test results fall short, switching to traditional workflows is recommended. An exception applies if the brand accepts stylized treatments, such as intentional color shifts or exaggerated lighting, in which case AIGC may suffice. However, the brand must confirm such stylistic deviations in writing.
Required materials from the brand and confirmation steps for the production team.
Brands must prepare a visual identity guideline containing standard color values, secondary colors, prohibited colors, and color combination examples. They should also provide reference frames from existing commercials or product images, indicating which visuals best match the desired brand color and lighting. If historical ads exist, final files or screenshots must be provided, specifying which shots to maintain. The production team must verify the completeness and currency of these materials, confirming whether brand colors have been updated and if reference frames are clear.
The production team must confirm communication objectives, target audience, and core selling points, as these influence lighting style. For example, tech products targeting youth may use high-contrast cool lighting, while household goods for families may use soft warm lighting. Delivery platforms must also be confirmed due to varying color management; for instance, web and TV have different color gamuts. Teams must remind brands to follow the latest official platform specifications prior to release rather than relying on outdated data.
Execution steps include the production team listing and confirming required assets at the project kickoff. The client must provide any missing materials within three days, or the project will be delayed. Based on provided assets, the team produces a style test video featuring various brand color and lighting options for client selection. Acceptance criteria require written client approval of the test video before formal production begins. A key risk is that incomplete client materials force the team to make assumptions, resulting in rework.
The delivery phase requires documenting color and lighting specifications in technical documentation.
Delivery involves more than just the final video file. Clients receive technical documentation recording brand color values, lighting parameters, grading node settings, model versions, and prompt summaries for each shot. This document supports future maintenance or version updates. If specific shots require modification, the team can use this documentation to quickly locate and adjust them. The document must include color profiles to ensure consistent playback across different devices.
The production team must deliver source files, including uncompressed masters, color grading project files, generated frame sequences, and reference image sets. Source files must be clearly named with shot numbers, version numbers, and dates. Clients must verify source file integrity, such as checking that project files open correctly and frame sequences are continuous. Delivery must also include an acceptance report listing all inspection items and results.
Specifically, the production team conducts internal quality checks before delivery, including color and lighting consistency tests. Upon receipt, clients review files on calibrated monitors against the technical documentation. Any issues must be reported within three days for correction by the production team. If clients fail to complete acceptance within the agreed timeframe, delivery is deemed accepted, and subsequent revisions may incur additional fees.
Summary of Applicable Boundaries and Next Steps
AIGC commercials are best suited for projects with flexible brand color tolerances, defined lighting styles, and clients willing to participate in early testing when ensuring color and lighting consistency. Caution is advised if clients cannot provide color and lighting references or require extremely high precision. Production teams should clarify these boundaries during the proposal stage to avoid later disputes.
We recommend clients first conduct a small-scale test using AIGC to generate 3–5 key shots to evaluate color and lighting consistency. If successful, proceed to full production; if not, adjust prompts, reference images, or post-production workflows, or revert to traditional methods. The production team should provide a test report with data and analysis to support decision-making. The entire process should be documented for future project reviews.
If you are preparing an AIGC commercial project, gather your brief, visual references, product or corporate materials, delivery platforms, and copyright scope before reviewing theAIGC Video Services pageTranslate abstract preferences into actionable production boundaries through communication.
