How Brands Should Handle Copyright and Compliance When Using AI for Content

"Can AI-generated images be used commercially?" "Will using AI in advertising lead to copyright infringement?" "Can AI music be directly embedded into brand videos?" "After purchasing IP licensing, can we use those characters for AI generation?"

These questions are popping up with increasing frequency across brand marketing, procurement, and content teams. While they all seem to ask about "copyright," the real issue isn't a single question—it's an entire end-to-end chain: where input assets come from, how models are trained and used, whether output resembles existing works, what third-party rights are introduced, whether watermarking/labeling is required at publication, and what verification materials suppliers must deliver at handover.

China's current Generative AI regulations explicitly require providers and users to respect intellectual property rights, portrait rights, privacy, and personal information rights. Furthermore, the Measures for Labeling AI-Generated and Synthetic Content (effective September 1, 2025) integrates explicit/implicit labeling and dissemination responsibilities into the regulatory framework. Heading into 2026, what brands truly need isn't just "a legal quick check after post-production," but a structured compliance workflow spanning assets, generation, publication, and delivery.

Step 1: Before Feeding Assets into AI, Clarify Exactly What Rights You Hold

The most common myth in AI content projects is confusing "possessing an asset" with "possessing all usage rights."

Brand product shots, spokesperson likenesses, IP characters, music, fonts, stock photography, user-generated content (UGC), and legacy commercials can all serve as inputs for AI generation, but their legal scopes differ significantly. Even if an asset was previously approved for advertising, that does not automatically grant rights for AI training, character replication, voice cloning, secondary generation, or new commercial media.

For brands, the core question is not simply "does this asset have copyright?" but breaking it down into specifics: Who is the licensor? What usage forms are permitted? In which regions, media, and timeframes? Is adaptation or derivative generation allowed? Can it be uploaded to third-party AI tools? Does it involve portrait, voice, or publicity rights?

WIPO's IP guidelines on Generative AI emphasize that enterprises using Generative AI must thoroughly understand tool terms of service, third-party data licenses, and potential IP risks. In filmmaking, WIPO's rights clearance guide warns that even if AI output doesn't directly enter the final edit, uploading scripts, video clips, or protected assets to third-party generation platforms can trigger data usage or broad licensing terms under platform agreements.

Therefore, having a license is not the end goal; what matters is verifying whether that license covers AI as a new mode of use.

Step 2: Model Capability Does Not Equal Commercial Rights for Brands

Once inside the generation stage, risk shifts from "asset ownership" to "whether the generation act exceeds boundaries."

Common pitfalls include: generating assets highly similar in style, composition, or character to protected works; using real human portraits, voices, or performances without explicit consent; exceeding agreed scopes when utilizing well-known IP characters; generating prompts that yield substantially similar visuals, audio, or text; and uploading unannounced products, scripts, or celebrity materials to third-party platforms with unclear data policies.

China's Interim Measures for the Management of Generative Artificial Intelligence Services require generative AI services to utilize legitimate data sources and foundational models, prohibiting infringement upon others' IP, portrait, privacy, or personal information rights. Furthermore, Supreme People's Court judicial opinions on AI disputes in 2026 state that when AI content infringes copyright, courts evaluate service types, training data origin, degree of user participation, necessary mitigation measures, and commercial profit. If a user knowingly leverages AI to generate substantially similar works without reasonable defense, they may bear liability.

This means that for brands, "it was generated by AI" is not an automatic legal shield.

A prudent production workflow must draw clear boundaries upfront: which elements can be directly referenced, which can only be abstractly styled, which must be created as fully original assets, and which must never enter third-party models. This pre-check is crucial for real people, celebrity IPs, voices, music, and high-recognition characters.

Step 3: In IP Projects, Copyright Cannot Be Solved by a Single License Agreement

IP co-branding is one of the most misunderstood categories in AI commercial content.

Securing IP partnership rights does not grant unrestricted usage across all visuals, characters, stories, music, and derivative expressions. Licensing scopes are often limited to product packaging, specific characters, designated media, limited regions, or fixed timeframes. Whether AI can generate new poses, scenes, or storylines depends on actual contract terms and approvals.

The Disney × F1 × MINISO campaign executed by FansAI is a prime example. The project involved multiple IP parties and strict licensing perimeters: F1 licensing focused primarily on product appearance without pre-packaged official promotional visual assets, while all content required multi-party review within a 7-day turnaround window. The critical upfront challenge was not merely "how to generate," but defining what could be expressed versus what could not, and crafting creative concepts within licensed boundaries.

Similarly, celebrity derivative IPs face multi-layered checks. An original character tied to a real celebrity involves character copyright, celebrity name/likeness associations, as well as existing music or brand assets. Without distinguishing "directly licensed assets," "abstract cultural elements," and "brand-new original character assets" prior to production, rework costs escalate exponentially near launch.

Hence, IP-related AI projects require embedding copyright rules directly into creative and production pipelines rather than saving them for the final legal review.

Step 4: Music, Voice, and Fonts Are the Most Easily Overlooked Risks

In AI video projects, copyright risks frequently occur not in the main visuals, but in secondary assets added late in production: music, voiceovers, and typography.

Whether AI-generated music can be commercially used depends on the AI music platform's terms of service, account/tier licensing, usage scope, and whether input reference tracks contained copyrighted audio. Voice cloning involves natural persons' publicity rights and explicit consent. Fonts, stock sound effects, and video templates also require commercial licenses regardless of screen size or duration.

For commercial projects, managing these as independent assets is essential: catalog sources and licenses for audio, retain font commercial certificates, explicitly define voiceover authorization scopes, and maintain procurement receipts for all third-party media.

This ensures that when a brand extends a campaign, switches platforms, releases overseas versions, or re-edits content later, every element remains legally verifiable.

Step 5: Before Launch, Check AI Content Watermarking & Labeling

Beyond copyright, brands face a concrete regulatory obligation: AI content labeling.

China's Measures for Labeling AI-Generated and Synthetic Content (effective September 1, 2025) covers AI-generated text, images, audio, video, and virtual scenes, enforcing both explicit (visible) and implicit (digital watermark) requirements. Furthermore, creators publishing AI content on public networks must declare AI usage and apply platform labeling features.

This does not mean every brand asset requires identical execution; requirements vary based on content type, platform, and usage scenario. Media, film, and artistic productions may follow specific industry guidelines.

Brands should include an AI labeling checklist item prior to publishing—specifying whether labeling is required, who adds it, and platform-specific rules—rather than assuming raw vendor deliverables are immediately ready to post.

Step 6: At Handover, Brands Need More Than Just an MP4 File

When an AIGC project completes, brands should receive a full chain-of-title documentation package alongside the final video.

Depending on complexity, this package should include: final renders and multi-cut files, source logs for key assets, brand/IP/portrait license agreements, font and music licenses, AI platform/model commercial subscription records, review/approval logs, AI watermark declaration records, as well as project source files and reusable asset libraries.

For sensitive projects involving unreleased products, celebrity assets, or proprietary IP reference images, clear contractual terms should dictate whether reference materials are stored or deleted, which tools accessed them, and future reuse rights.

This provides a practical standard when evaluating AIGC vendors:

A mature AI content vendor shouldn't just prove "what they can generate," but also clearly demonstrate "where assets come from, how rights are managed, and how compliance is delivered."

Brand AI Content Copyright Checklist

To simplify this for procurement and marketing teams, use this quick verification matrix:

Stage	Core Question to Confirm
Input Assets	Do brand, IP, portrait, music, font, and UGC assets have licenses valid for AI processing in this project?
AI Tools	Does the platform agreement permit current commercial use? Are data privacy terms acceptable for uploaded inputs?
Generation	Is there risk of substantial similarity, unauthorized voice cloning, or character/portrait infringement?
IP Co-branding	Does licensing cover AI generation, derivative adaptation, media type, region, duration, and specific character assets?
Pre-Launch	Are music, font, stock media, portrait, and IP checks complete? Is AI content labeling required?
Handover	Are licenses, source logs, approval records, tool terms, source files, and asset deletion agreements fully retained?

While this table does not replace formal legal counsel, it helps teams spot and resolve major legal roadblocks early in procurement and production.

Integrating Copyright into Content Production

AI drastically accelerates content creation, but it also amplifies speed-related risks: when asset ingestion, visual generation, and multi-version iteration happen rapidly, unverified legal permissions multiply error rates across channels.

Compliance must not be treated as a final post-production hurdle.

A streamlined workflow follows this order:

Licensing defines what enters, creativity dictates expression, technology governs generation, compliance enables publication, and deliverables secure future reuse.

This represents the core capability modern brands and AI content agencies must build together.

Conclusion: Brands Need Results That Are "Safe to Deploy"

For brands, the true value of AI content lies beyond speed.

An image, video, or audio track creates true commercial value only when it can safely go live, run in paid media, scale across regions, and reside permanently in brand asset libraries.

Thus, "Is AI content copyrightable?" cannot be answered with a simple yes or no. The precise question to ask is:

What specific rights apply to the inputs, models, personalities, IP, music, and final deliverables used here—and what enduring commercial licenses and proofs does the brand actually hold?

AI makes production faster.

Commercial content, however, requires speed that remains entirely safe to use.