Protect a game project’s confidential data by deciding what staff may submit before they use an AI tool, approving specific workflows and accounts, and checking how each feature handles prompts, files, and outputs. Do not assume that a paid plan, a “no training” statement, or a vendor’s name alone makes a workflow safe.
Unreleased code or assets should go into an AI tool only when the studio has explicitly approved that exact tool, account, feature, and data category—and verified the applicable settings and contract. Otherwise, keep the material out and use a redacted excerpt, synthetic example, or general description instead.
Set rules for what data staff may submit
Start with a classification scheme the studio can apply consistently. A practical set of categories is public, internal, confidential, and restricted, but adapt the labels to the studio’s existing policy. Make clear that classification determines whether AI use is allowed, which services can be used, and what must be removed or transformed first.
Include the material that makes a game project sensitive, not just conventional business files:
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- Confidential: unreleased art and audio, characters and environments, dialogue and scripts, design documents, localization files, monetization plans, and production schedules.
- Restricted: source code and build pipelines, credentials and signing certificates, player or employee personal information, publisher or partner files, and contractor deliverables subject to restrictions.
- Any category with a third-party obligation: flag contractual, publisher, platform, or partner limits explicitly. A studio’s permission to use information does not automatically mean it has permission to send it to a vendor.
NIST’s 2024 Generative AI Profile identifies governance, data protection, retention, incident response, and monitoring as relevant considerations. The game-specific labels above are a practical studio policy, not categories prescribed by NIST.
Approve workflows, not just AI vendors
One brand may offer consumer and business products with different terms; one product may also handle data differently across chat, file uploads, web search, code tools, projects, memory, agents, and connected apps. Maintain an approved-use register for the actual workflow rather than a list of vendor names.
For each approved workflow, record:
- The service, account type, workspace, and administrator.
- Allowed data classes and any required redaction or transformation.
- Enabled features, including uploads, search, code execution, memory or project spaces, integrations, and agents.
- Retention and training settings, data location requirements, and applicable contract owner.
- The review date and the person responsible for reassessing it.
NIST’s SP 800-218A, published in 2024, is a secure software-development profile for generative AI and dual-use foundation models. NIST says it should be used with the Secure Software Development Framework, SP 800-218; it is a framework resource, not a ready-made approval policy for a game studio.
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Check training, retention, and feature scope separately
“Not used for model training” and “not retained” are different promises. Training describes whether submitted content may be used to improve models; retention concerns whether prompts, outputs, files, or related records are kept. A tool can make one commitment without making the other. Check both, and ask what happens to application state, logs, conversation history, human review, and content sent through integrations.
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- Can prompts, outputs, uploaded files, or feedback be used to train or improve models? Does the answer depend on account type or an opt-in or opt-out setting?
- What is stored in abuse-monitoring logs, chat history, project workspaces, local transcripts, files, or audit systems—and for how long?
- Can administrators set retention or request zero retention? Which organization or account types qualify?
- Do the same controls apply to the exact model, endpoint, file feature, search, code tool, agent, and connected services in use? Are there exclusions or safety-related exceptions?
- Where is content processed and stored? What do the contract, data-processing terms, subprocessors, and incident-notification commitments say?
Vendor statements illustrate why checking the exact product matters; they are not endorsements or independent comparative certifications. OpenAI says inputs and outputs for ChatGPT Enterprise, Business, Edu, Healthcare, Teachers, and API are not used for training by default, and describes encryption, access controls, and retention choices for qualifying organizations on its business data privacy page. Separately, OpenAI’s API data-controls documentation says default abuse-monitoring logs may contain customer prompts and responses and are retained for up to 30 days. Zero Data Retention and Modified Abuse Monitoring require approval, and feature or endpoint limitations apply. That duration describes OpenAI’s stated API policy, not a general rule for AI services.
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Anthropic’s API and data retention documentation describes different retention by feature. Its June 9, 2026 zero data retention scope explanation says the arrangement applies only to eligible APIs and specified commercial Claude Code products, with organization-level enablement and safety-related exceptions. Other surfaces, local transcripts, and some records follow different models. Recheck the current documentation and agreement for the precise product and configuration you intend to use.
Minimize what goes into the prompt
Even an approved workflow should receive only what it needs. Separate the problem from proprietary details, and use synthetic examples, fictional names, locally generated test cases, or short redacted excerpts wherever they will work.
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For example, instead of pasting an unreleased quest script, describe the structural problem with invented characters and sample dialogue. Instead of uploading a repository to debug a function, share the smallest approved, redacted excerpt that reproduces the issue. If the question can be answered without the confidential detail, leave it out.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Restrict access and connected tools
Use managed work accounts for approved workflows, limit workspace membership, grant only the permissions needed, and remove access promptly when staff or contractors leave. Disable integrations and third-party tools that the workflow does not require; a connected search, file, code, or agent feature may send information to another processor.
Where the chosen product supports them, use MFA, SSO, role-based controls, audit logs, usage visibility, and centralized administration. OpenAI lists these kinds of controls for applicable business or API offerings on its business data privacy page, but availability depends on the product. Access controls help a studio govern who can use a workspace and review usage; they do not determine what a provider retains after receiving content.
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Keep an approval and incident process
Name an owner for approvals and periodic reviews. Reassess a workflow when the vendor changes product behavior, retention terms, or feature scope, and record the review date. A compact provider review should cover these comparison points:
| Area | What to verify |
|---|---|
| Training and improvement | Whether prompts, outputs, files, or feedback may be used, and whether rules vary by account or setting. |
| Retention | Logs, files, project storage, application state, transcripts, retention duration, deletion, and administrative controls. |
| Feature scope | Whether the actual model, endpoint, upload, search, code, agent, and integration inherit the same protections. |
| Access and oversight | MFA or SSO, administrator roles, audit or usage logs, group controls, and offboarding. |
| Contract and geography | Data-processing terms, subprocessors, incident commitments, processing or storage region, and third-party restrictions. |
| Operational fit | Whether staff can complete the approved work without submitting restricted data, and whether the studio can enforce the rules. |
If confidential material is submitted accidentally, notify the studio’s security or privacy contact, preserve relevant details, and follow the provider’s deletion or support process where available. Rotate any exposed secrets, then have the responsible team assess contractual and partner notification duties. Applicable legal obligations depend on jurisdiction and contract. NIST’s Generative AI Profile includes incident response, monitoring, tracking, and documentation among its governance considerations.
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