Treat each AI-assisted asset as a production item that needs a source record, a defined use, and human review before release. Keep the record with the project, inspect the output for problems, and check the terms that apply to the tool, collaborators, platform, and distribution plan. Documentation helps a team make and explain decisions; it does not guarantee that an asset is lawful, original, exclusive, or safe to publish. For a complementary perspective, see the game jam rules checklist.
Key Takeaways - Record the tool, date, inputs, edits, intended use, and reviewer for each asset. - Review outputs for recognizable material, unclear sources, and conflicts with project or platform requirements. - U.S. Copyright Office guidance addresses copyrightability and human authorship in the United States; it does not settle every legal question or jurisdiction.
Build an asset record that travels with the project
For each image, audio file, text passage, model, or other generated material, record its filename, tool and version if known, creation date, prompt or source inputs where appropriate, edits, intended use, and reviewer. Note whether a human made original expressive contributions and where those contributions appear. Keep contracts, licenses, receipts, and source files for third-party material alongside the record.
Use a consistent identifier in the project so a shipped asset can be traced back to its notes. When an asset is substantially revised, preserve the earlier version and describe the change. Avoid recording sensitive or confidential inputs in a shared log unless the team has permission to store them there.
Review the output before it enters a build
A provenance record is not an originality check. Review the asset itself for recognizable characters, logos, distinctive costumes, protected artwork, real-person likenesses, misleading text, and other material that could raise rights, consent, or platform concerns. Compare it with the references and inputs used to create it. If an asset is uncertain, hold it out of the release build while the team investigates or replaces it.
Check the service terms and any relevant licenses for the intended use, including commercial use, attribution, redistribution, and restrictions on input or output. These terms can differ by provider and change over time. Also check contributor agreements, publisher requirements, marketplace policies, and the destination platform’s disclosure rules. Do not treat a model’s statement about rights as a legal determination.
What the U.S. Copyright Office says about authorship
The U.S. Copyright Office’s January 29, 2025 news release summarizing Part 2 of its Artificial Intelligence report says that copyright can protect AI-assisted output where a human author determined sufficient expressive elements. It gives examples such as human-authored material perceptible in the output or human creative arrangements or modifications, and says that the mere provision of prompts is not enough. The full report addresses copyrightability of generative AI outputs under U.S. law.
This is a statement about the U.S. Copyright Office’s position on copyrightability, not a universal rule about all rights in an asset. It does not decide whether an output infringes someone else’s work, whether a provider’s terms permit a use, or how publicity, privacy, contract, or other laws apply. The Office also describes its conclusions in the context of existing U.S. copyright principles and discusses case-by-case assessment of human contributions. Laws, court decisions, and facts differ across jurisdictions and may change.
Use a release review, not a blanket safety label
Before release, have a reviewer who understands the project check the asset record, the output, the license or terms, any required credit or disclosure, and any unresolved concerns. Keep a replacement option for assets that cannot be cleared to the team’s standard. Escalate questions that materially affect commercial distribution to qualified counsel in the relevant jurisdiction.
This checklist is general production hygiene, not legal advice. A clean record can make review more reliable, but it cannot turn an uncertain asset into a cleared one. Make the release decision based on the specific asset, the specific use, the applicable terms, and the places where the game will be distributed.
A practical provenance record for a single asset
A useful record answers four questions: where did the file come from, what went into making it, how has the team changed it, and where will it be used? A team can keep these fields in a spreadsheet, asset-management tool, or a simple project document:
| Field | Example of what to record |
|---|---|
| Asset identity | Project path, filename, and version or hash |
| Origin | Human-created, AI-assisted, licensed library, commissioned, or mixed |
| Tool or supplier | Provider and model or product version if known |
| Inputs | Prompt summary and references, subject to confidentiality and consent limits |
| Human changes | Editing, compositing, drawing, retouching, selection, or other contributions |
| Intended use | In-game background, icon, character, store image, or marketing material |
| Review | Reviewer, date, and questions checked |
| Terms and disclosure | Relevant service terms, license, attribution, or platform statement |
This is a production record, not a legal conclusion. A complete log cannot guarantee that a file is original, non-infringing, copyrightable, or accepted by a marketplace. It does make it easier to locate the source and understand the team’s decisions if a question arises later.
For example, a generated background may be used only as a temporary mood reference, while a human-created version becomes the shipped asset. The record should reflect that distinction so the temporary file is not accidentally included in the release build. If the team edits a generated image substantially, note what changed and preserve working files that explain the process where appropriate. Do not include confidential prompts or personal data in a shared record unless the team has a sound basis to store them.
Review rights, consent, and platform requirements separately
Different concerns need different checks. A recognizable logo or character raises a different question from whether a service permits commercial use. A real-person likeness raises consent and publicity considerations. A sound sample may have a license that differs from an image license. A submission platform may request disclosure even when the team believes an asset is otherwise permitted.
Review the actual output and the inputs that shaped it. Look for distinctive protected material, copied branding, misleading text, sensitive or private content, and unintentional likenesses. Check the terms that apply to both the tool and the asset’s intended use. Then check contributor agreements, publisher rules, marketplace terms, and the destination platform’s disclosure requirements. These documents can change, so use the terms in force for the actual project and distribution plan.
If the team cannot resolve a concern, hold the asset out of the release build while it investigates or replaces the material. A provenance log helps the team identify alternatives; it does not turn uncertainty into clearance.
Interpret U.S. Copyright Office guidance narrowly
The U.S. Copyright Office’s guidance on AI and copyright addresses questions within U.S. copyright law, including human authorship and the role of human contributions. It should not be summarized as a blanket rule that all AI-assisted material is either protected or unprotected. The analysis can depend on the specific work and the human contribution involved. Copyrightability is also distinct from whether use of an output may raise other legal or contractual issues.
A production team should therefore preserve information that helps explain its process: original sketches, human edits, selection and arrangement decisions, layered project files, and notes about which parts were generated or changed. This information may help a team describe its contributions accurately. It does not guarantee registration, exclusivity, or a particular legal outcome. For cross-border distribution, the U.S. guidance should not be treated as a substitute for checking the laws and requirements relevant to other jurisdictions.
A release review that can be repeated
Before shipping, compare the final build against the asset log. Confirm that every included external or AI-assisted asset has an owner and a recorded source. Check credits, attributions, and disclosures against the current platform instructions. Remove unused files that could be mistaken for final assets. Make sure the team has the files and permissions it needs to maintain or replace each asset.
When a new version of an asset enters the build, repeat the relevant review. A change in prompt, reference, editing, or usage can change the questions the team needs to answer. Keep the review focused on actual assets and actual distribution plans rather than relying on a generic “AI safe” label.
Does keeping a prompt prove that an AI-generated asset is lawful?
No. A prompt is one piece of provenance information. It does not establish that every input was authorized, that the output avoids protected material, or that a service’s terms meet the project’s needs.
Can a team use AI-generated assets commercially?
The answer depends on the tool’s current terms, the asset, the relevant law, and the planned use. Check the terms and the project context rather than relying on a general statement about AI-generated content.
Handle a takedown, question, or uncertain source
If a platform, player, publisher, or contributor raises a concern, preserve the relevant build and asset records before changing files. Identify the exact asset and where it appears, then review its source, inputs, editing history, license, and intended use. Keep communication factual and avoid speculating about a person’s motives or making promises the team cannot support. If the concern involves potential legal exposure, consult qualified counsel rather than treating an internal checklist as a legal opinion.
For a small team, the immediate production decision is often narrower than the legal question: should this asset stay in the public build while the team investigates? A reversible step such as replacing or temporarily removing the asset can reduce confusion while the source is reviewed. Document who made the decision and what information remains missing. If the asset is cleared or replaced later, update the record so the team can explain which version was distributed.
Keep claims about copyright and ownership precise
Avoid marketing language that promises exclusive ownership or automatic copyright protection for all generated material. Distinguish the team’s original human work, licensed materials, AI-assisted components, and uncertain material. If a project has a publisher or commercial partner, check the contract language they require and have the appropriate person approve any representation about rights.
When describing a process publicly, explain what the team actually contributed. For example, it may have written a prompt, selected among outputs, painted over parts, combined elements, or produced a new asset from a reference. Those details help readers understand the workflow without asserting a legal result. Preserve source files and meaningful edits where appropriate, but do not claim that a particular amount of editing guarantees a specific outcome.
A source record should also distinguish license questions from copyright questions. A provider’s terms may grant certain contractual permissions, but those terms do not necessarily answer every question about third-party rights, attribution, privacy, or platform rules. Similarly, a copyright analysis does not automatically determine whether a service contract or marketplace policy has been followed. Assign each question to the right review path.
