LLM clause: Copy, customize, and use instantly

Introduction

An LLM clause (Large Language Model clause) governs the use of AI models—like GPT, Claude, or similar systems—in the context of contract performance, data handling, content generation, or decision-making. It promotes transparency, sets boundaries on use, and helps mitigate legal, ethical, or confidentiality risks.

Below are templates for LLM clauses tailored to different scenarios. Copy, customize, and insert them into your agreement.

LLM clause with disclosure requirement

This version requires parties to disclose if AI tools are used.

Each party agrees to disclose in writing if any content, analysis, or recommendations provided under this agreement were generated using a large language model (LLM), including but not limited to OpenAI, Anthropic, or similar AI systems.

LLM clause with prohibition on LLM use

This version completely bans use of LLMs.

Neither party shall use any large language model (LLM) for generating, analyzing, or processing content under this agreement without prior written consent from the other party.

LLM clause with confidentiality safeguard

This version restricts use of LLMs with sensitive data.

No party shall input, upload, or transmit confidential, proprietary, or personally identifiable information into any large language model system unless such system is self-hosted, securely isolated, and approved in writing by the disclosing party.

LLM clause with audit rights

This version allows review of AI-assisted work.

Either party may request a record or audit of content created or influenced by large language models during the term of this agreement, to ensure compliance with intellectual property, confidentiality, and usage policies.

LLM clause with permitted use cases

This version defines specific allowed uses.

Use of large language models (LLMs) shall be permitted solely for internal drafting assistance, idea generation, or formatting support. LLM outputs shall not be relied upon for final legal, financial, or compliance decisions.

LLM clause with IP ownership clarification

This version addresses IP rights for AI-generated content.

All content generated through or with the assistance of large language models under this agreement shall be considered "works made for hire" and owned exclusively by the commissioning party, subject to applicable copyright law.

LLM clause with human review requirement

This version mandates human oversight.

Any output generated by a large language model (LLM) must be reviewed and approved by a qualified human representative before being submitted, published, or relied upon under this agreement.

LLM clause with risk allocation

This version assigns responsibility for AI use.

Each party assumes full responsibility for any errors, omissions, or legal consequences resulting from its use of large language models in connection with this agreement.

LLM clause with training data limitation

This version prohibits data reuse for training.

Neither party may use content, documents, or data shared under this agreement to train, fine-tune, or otherwise enhance any large language model unless expressly authorized in writing by the disclosing party.

LLM clause with indemnity for misuse

This version includes indemnification.

A party that uses a large language model in violation of this agreement shall indemnify and hold harmless the other party from any claims, losses, or liabilities arising out of such unauthorized or improper use.

LLM clause with usage transparency log

This version requires maintaining a log of all LLM use.

Each party agrees to maintain an internal log of all instances where a large language model was used in relation to this agreement, including the tool used, purpose, and a summary of outputs generated.

LLM clause with attribution requirement

This version mandates disclosure of AI involvement in content.

Any deliverables partially or wholly generated using large language models must clearly state the involvement of AI in their creation unless waived in writing by the receiving party.

LLM clause with client opt-out option

This version allows the client to prohibit LLM use per project.

The client reserves the right to prohibit the use of large language models on a project-by-project basis, which must be honored upon written request.

LLM clause with no third-party model reliance

This version limits use to internally managed models.

Only large language models hosted and operated within the party’s own secure infrastructure may be used for any purpose under this agreement. Third-party cloud-based LLMs are prohibited without written consent.

LLM clause with bias mitigation clause

This version targets ethical risks.

Any content generated using a large language model must be reviewed for potential bias, misinformation, or discriminatory language. Parties shall act to mitigate any identified risks before distribution or use.

LLM clause with jurisdictional restriction

This version limits where AI models may be hosted.

No LLMs hosted in jurisdictions with conflicting data protection laws may be used in connection with this agreement without prior written approval from both parties.

LLM clause with LLM-free deliverable guarantee

This version commits to human-only output.

All deliverables under this agreement shall be created solely by human contributors. No AI-generated content or assistance via LLMs shall be used in any part of the process.

LLM clause with defined review interval

This version mandates periodic review of LLM-related risks.

The parties agree to review this LLM clause at [X]-month intervals during the term of the agreement to evaluate changes in technology, legal requirements, or risk levels.

LLM clause with technical documentation handover

This version requires disclosure of AI process.

Upon request, any party using an LLM to produce deliverables shall provide documentation describing the AI system used, its configuration, and post-processing steps applied to the output.

LLM clause with training dataset exclusion

This version ensures contract data won’t be used for AI training.

Content exchanged under this agreement shall not be included in any training dataset for LLMs, either directly or indirectly, unless express written permission is granted.

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LLM clause with knowledge cut-off consideration

This version requires validating outdated AI content.

Where an LLM is used to generate outputs, the party relying on the output must independently verify facts, legal references, or market data that may be outdated due to the model’s training cut-off date.

LLM clause with LLM supplier vetting

This version requires due diligence on AI vendors.

Parties must ensure that any third-party provider of LLM services has undergone appropriate due diligence, including evaluation of their security, privacy, and content policies.

LLM clause for internal-only experimentation

This version permits sandboxed use only.

LLMs may only be used internally for experimental or developmental purposes, and outputs must not be shared with clients or external stakeholders without explicit approval.

LLM clause for prompt recordkeeping

This version requires saving inputs.

All prompts or queries submitted to large language models under this agreement shall be recorded and retained for audit purposes for a minimum of [X] months.

LLM clause with employee usage training

This version mandates AI awareness.

Any employee or contractor intending to use an LLM in connection with this agreement must complete training on responsible and compliant use before proceeding.

LLM clause with cybersecurity risk protocol

This version ties LLM use to security standards.

Use of large language models must be evaluated for cybersecurity risks, and all outputs must be scanned for malicious code or embedded tracking elements before distribution.

LLM clause with no output substitution

This version forbids silent replacement of human content.

AI-generated content may not be used as a substitute for previously approved human-authored material without full disclosure and client consent.

LLM clause with limitations on automated decision-making

This version sets boundaries on decision automation.

No decisions affecting contractual rights, pricing, performance ratings, or legal positions shall be made solely on the basis of outputs from a large language model.

LLM clause for customer-facing output limits

This version restricts LLM use in client materials.

Parties shall not use LLM-generated language in customer-facing materials—including emails, contracts, or reports—unless such content has been approved by a designated reviewer.

LLM clause with litigation hold exception

This version pauses LLM use during disputes.

In the event of litigation or formal dispute, all use of LLMs in relation to this agreement shall cease unless specifically authorized by legal counsel.

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LLM clause for red-teaming accountability

This version requires testing for risk scenarios.

Parties using LLMs shall conduct periodic red-teaming exercises to assess the potential for harmful, biased, or inaccurate outputs and must log the results of such tests.

LLM clause with derivative work restrictions

This version clarifies IP control.

Parties agree that LLM-generated outputs shall not be adapted or distributed as derivative works without mutual consent and clear documentation of authorship and input sources.

LLM clause with consent-to-publish mechanism

This version governs use of AI in marketing copy.

Any use of LLM-generated material in public-facing channels—including case studies, blogs, or ads—must be approved in advance and clearly marked if generated by AI.

LLM clause with backup retention limits

This version restricts retention of AI data.

Any backups containing LLM-related prompts or outputs must be securely deleted within [X] days unless retention is required for audit or regulatory compliance.

LLM clause with traceability standard

This version requires traceable sourcing.

Parties using LLMs must ensure traceability of generated outputs to the source model, input prompts, and the responsible user or system.

LLM clause with copyright disclaimer for AI output

This version disclaims originality.

The parties acknowledge that content generated by LLMs may not qualify for copyright protection and agree to bear the risk of third-party use or replication.

LLM clause with alignment to ethical AI principles

This version ties use to ethical frameworks.

Any use of LLMs must be consistent with widely accepted AI ethics guidelines, including fairness, transparency, non-discrimination, and accountability.

LLM clause with jurisdiction-specific AI compliance

This version enforces local rules.

Each party agrees to comply with any country- or state-specific laws regulating the use of LLMs, including but not limited to disclosure, bias mitigation, and transparency rules.

LLM clause with emergency shutdown protocol

This version includes kill-switch requirements.

Parties using LLMs in automated processes must implement an emergency shutdown mechanism that allows immediate deactivation in the event of malfunction or breach.

LLM clause with legal disclaimer for outputs

This version distances liability for AI content.

Outputs generated using large language models shall not be construed as legal, financial, or professional advice, and each party shall apply independent judgment before relying on such outputs.

LLM clause with multi-model declaration

This version requires disclosing the models used.

Where multiple LLMs are used for content generation, the parties agree to disclose which models contributed to which outputs, upon request.

LLM clause with third-party rights check

This version ensures outputs don’t infringe.

All outputs generated using LLMs must be screened for inclusion of third-party proprietary or copyrighted material prior to publication or delivery.

LLM clause with zero hallucination tolerance

This version disallows inaccurate AI content.

Any hallucinated or fabricated statements generated by an LLM must be discarded, and no such content shall be used or relied upon in any part of the agreement.

LLM clause with sandbox testing zone

This version limits AI experimentation to safe areas.

Any LLM testing, prompt engineering, or fine-tuning must be performed within a designated sandbox environment that is isolated from production systems.

LLM clause with third-party indemnification waiver

This version protects against upstream model issues.

Each party acknowledges that LLM providers may disclaim liability for the content their systems generate, and agrees not to seek indemnity from the other party for upstream AI errors.

LLM clause with user authentication requirement

This version restricts who can use LLMs.

Only authorized individuals may access or use LLMs in relation to this agreement. Shared accounts, anonymous access, or public tools are strictly prohibited.

LLM clause with testing data segregation

This version keeps test data isolated.

Any datasets used to test or prompt LLMs under this agreement shall remain segregated from production datasets and not be used to generate final deliverables.

LLM clause with no influence on binding terms

This version keeps contracts human-validated.

No LLM-generated content shall be deemed binding under this agreement unless expressly reviewed and approved by human parties authorized to negotiate on their behalf.

LLM clause with notice before deployment

This version requires pre-deployment warning.

Before integrating an LLM into a business process governed by this agreement, the party must give [X] days’ written notice and allow for evaluation by the other party.

LLM clause with future tech reevaluation clause

This version anticipates AI advancements.

The parties agree to revisit this clause and update LLM governance terms if materially new capabilities, risks, or regulatory standards emerge during the agreement term.

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This article contains general legal information and does not contain legal advice. Cobrief is not a law firm or a substitute for an attorney or law firm. The law is complex and changes often. For legal advice, please ask a lawyer.