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Before using an AI tool on a film or TV production, evaluate the specific task and the material it will handle—not just the tool’s name. Confirm that the use is authorized for the project and covered by the applicable agreements, check how the vendor handles inputs and outputs, obtain any required consent, and have a responsible person review the results. Keep a record of the tool and how it was used. The right requirements depend on the production, role, jurisdiction, contract, and use case.
What should a production assess before approving an AI tool?
Start with the proposed use, not a general judgment that a particular tool is “approved” or “safe.” A system that summarizes non-sensitive notes raises different questions from one that processes a script, generates production imagery, or reproduces a performer’s voice or likeness. The same product may therefore be acceptable for one task and unsuitable for another.
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Write down what the tool will do, what material it will receive, what it may produce, and how people will use that output. Then identify who has authority to approve the use and who remains accountable for the decisions that follow. This framing helps a production uncover contract, privacy, rights, security, and creative concerns before anyone uploads material or relies on a result.
- Task: What department is using the tool, and what result is expected?
- Material: Will it receive confidential production information, creative work, personal information, or performer-related material?
- Output: Is the result exploratory, an aid to a human decision, or intended for delivery?
- Authority: Who can approve the tool and this exact use on this production?
- Accountability: Who will review, correct, document, and take responsibility for the result?
How do you define and scope the proposed use?
A useful proposal describes one bounded task in terms the production can approve or reject. Avoid requests such as “use AI in post” or “try an AI workflow”: they do not identify the material involved, the intended output, or the decisions a person will make with it.
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Describe the task
Record the department, the intended result, the people who will use the output, and whether it is exploratory or may become part of a production deliverable. Say whether the tool is being asked to summarize, classify, transform, generate, or imitate material. Be specific about whether the work touches a creative element or a person’s identity or performance.
Inventory the inputs and outputs
List the material that would go into the system: for example, notes, scripts, reference images, recordings, or other production material. Identify whether any of it is confidential, personally identifiable, or subject to a license or other restriction. Treat generated results as production material too: establish who may use them, how they will be reviewed, and whether they could reproduce protected or performer-related material.
Decide what success means
Before a trial, describe what a useful result must do and what would make it unacceptable. Criteria can include accuracy, creative suitability, reliability across representative inputs, workflow fit, and the amount of human correction required. These are practical evaluation questions, not a standardized industry benchmark.
Who needs to approve the use on a production?
Approval depends on the actual production policy, contract, role, and jurisdiction. Check the relevant project rules and agreements with the production’s authorized decision-maker and, where needed, the appropriate contract administrator before a pilot or live use.
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Published agreements and policies offer examples, not universal rules. The Directors Guild of America’s summary for episodic television and high-budget SVOD series says employers may not use generative AI in connection with creative elements without consulting the director. That point should be applied within the scope of the relevant agreement, not assumed to govern every production or crew member. The DGA lists agreements by coverage, so confirm which agreement and role apply to the work.
SAG-AFTRA’s AI resources describe a framework centered on consent, fair compensation, and control over performances. Those protections are relevant when a proposed task concerns covered work or performers, but the terms that apply depend on the current agreement and the production. A studio’s internal rules are similarly project-specific: Amazon MGM Studios’ published production policy requires both an approved tool and an approved use case for its own production context. Neither that policy nor a guild summary automatically sets the rules for a different production.
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Check for additional requirements from a client, distributor, production company, or other authorized party. If it is unclear whether a proposed use is covered, resolve that uncertainty before sending material to a vendor or allowing an output to influence production decisions.
What vendor terms and rights should you check?
Review the terms that govern the particular service and account before sharing production material. The important question is what happens to each input and output—not merely whether the tool can perform the requested task.
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- Retention and deletion: How long are prompts, uploads, references, and outputs kept? Can they be deleted, and what limits apply?
- Access and confidentiality: Who can access the material, including vendor personnel or other parties, and what confidentiality commitments apply?
- Training and reuse: May the vendor use submitted material or generated outputs to train or improve systems, or for other purposes?
- Rights and permitted uses: Do the production and vendor have the necessary rights for the inputs, references, and intended use of the outputs?
- Security and onward use: What protections apply to stored or processed material, and can it be shared with other providers?
- Disclosure and delivery: Do applicable contracts, policies, or delivery requirements call for disclosure or other records?
The Archival Producers Alliance’s September 2024 guidelines recommend legal review of licensing, labor obligations, publicity rights, copyright, errors-and-omissions coverage, disclosure, and international law. Those areas can inform a review, but they do not replace advice on the production’s own facts and agreements. Pact’s guidance for UK producers also identifies transparency, accountability, diversity, privacy, copyright, and human creativity as concerns. Its UK context should not be treated as a substitute for the law or contracts governing a production elsewhere.
How should a production handle a performer’s voice, likeness, or performance?
Pause and escalate any use that scans, reproduces, modifies, or generates a person’s voice, likeness, performance, or biometric information. Establish what the system does with that material and check the applicable consent, use, compensation, retention, and access requirements before proceeding.
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For a proposed use involving a performer or identifiable person, put the exact proposed activity in front of the authorized production and labor contacts. Distinguish among using existing material as a reference, modifying a recorded performance, creating a replica, and generating a synthetic performance; those are different uses that may raise different questions. Do not proceed on an assumption that consent for one use covers another.
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How can you run a bounded pilot?
A pilot should answer a narrow production question without exposing material or creating commitments the production has not approved. Use only material cleared for the trial, and agree in advance on evaluation criteria and who will review the results.
- Get approval for the pilot’s scope. State the task, tool, proposed inputs, reviewers, and whether results may affect production decisions. Confirm the approval chain and any agreement or policy requirements first.
- Select representative, permitted material. Use an approved sample that resembles the real task. Do not substitute confidential scripts, performer data, or other sensitive assets unless their use has been cleared.
- Compare candidates on the same task. Keep the task and review criteria consistent so that differences in results can be judged meaningfully. Do not describe the comparison as a validated industry test.
- Have a human assess the outputs. Review factual accuracy, suitability for the intended purpose, reliability, and the amount of correction needed. Decide in advance what errors or uncertainties make a result unusable.
- Record the decision. Capture what was tested, who reviewed it, what limitations emerged, and whether the production approved, restricted, or rejected the proposed use.
Use a scorecard that helps a production make its own decision rather than implying a universal rating system:
| Evaluation area | Question to record |
|---|---|
| Authorization | Is this tool and this exact use authorized for the production and covered by the applicable agreements? |
| Data and vendor terms | What material enters the service, and what may the vendor retain, access, train on, or reuse? |
| Rights and consent | Are permissions in place for the inputs and intended outputs, including any performer-related material? |
| Output quality | Does the result meet the agreed criteria under human review, and where does it fail? |
| Workflow and oversight | Who checks and corrects the result, and how much effort does that require? |
| Cost | What is the total cost for the proposed workflow, including review and correction? |
No universal rating scale or validated numerical benchmark for comparing production AI tools is established by the cited materials. The value of the scorecard is that it makes trade-offs and unresolved questions visible to the people responsible for the decision.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How should crews review and document AI output?
A person should review an output before it drives a production decision or reaches delivery. Review should match the task: check factual claims for accuracy, creative material for suitability, and any transformation or generation for unintended changes or problematic content. If the reviewer cannot tell whether the output is reliable enough for its intended purpose, do not treat it as ready for use.
Keep a decision trail that can explain what happened without implying that the tool made the production’s creative or operational decision. Amazon MGM Studios’ policy calls for human quality review and records of tools, prompts, references, and human creative decisions in its own production context. A production can use those as practical recordkeeping categories while confirming its own requirements.
- The approved task and scope of use.
- The tool and version, where available.
- The prompts, references, and other material used, subject to applicable confidentiality and retention rules.
- The reviewer, revisions, and material human decisions.
- Which elements were AI-generated, human-created, or materially changed during review.
Store these records in a way that respects the same confidentiality, access, and retention restrictions as the underlying production material. The record should make it possible to identify the use and human review without creating unnecessary copies of sensitive inputs.
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What are the most common reasons to stop or escalate?
Stop the proposed use or seek an authorized decision when a basic condition remains unresolved. A fast pilot is not a reason to bypass the production’s approval process or share material before its use is cleared.
- No one can identify who has authority to approve the task.
- The tool’s terms do not clearly establish retention, access, training, deletion, confidentiality, or onward use.
- Rights or permissions for input material or intended outputs are uncertain.
- The task involves a performer’s identity, performance, or biometric data and applicable consent or contract terms have not been checked.
- The output cannot be reviewed adequately, or the production has no clear person accountable for correcting it.
- The proposed trial would use material outside the approved scope or could be mistaken for an authorized deliverable.
Escalation may mean revising the task, choosing different material, limiting access, obtaining a needed approval, or declining to use the tool. The appropriate response depends on the production’s governing requirements; there is no single studio policy that resolves every case.
Frequently Asked Questions
Does a production have to disclose when it used AI?
There is no single disclosure rule established for every production or use in the cited materials. The Archival Producers Alliance guidelines identify disclosure as an issue for legal review, so check the project’s contracts, policies, and delivery requirements rather than assuming either that disclosure is always required or never required.
Is traditional AI treated the same as generative AI in union agreements?
Not necessarily: SAG-AFTRA’s 2023 generative-AI guide discusses distinctions between generative AI and traditional AI, along with specific agreement provisions. It is historical guidance, so verify the current agreement and the exact use before relying on any detail from it.
Can a crew member use a personal AI account for production work?
The cited materials do not establish a blanket rule about personal accounts. Before using one, check whether the production authorizes the account and whether its data, confidentiality, retention, and rights terms are acceptable for the material involved.
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