AI/ML Tools Terms of Service

AI Tool Terms Need AI-Specific Provisions

Generic SaaS terms don't address output ownership, training data rights, or hallucination disclaimers. I check for the provisions that matter when you're shipping AI.

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Sergei Tokmakov, Esq. California Bar #279869 · AI & Tech Contracts

The 6 AI Provisions I Check First

Beyond standard SaaS - these are what make AI terms bulletproof

Output Ownership

Who owns AI-generated content? What license do users get for outputs? Can you use outputs to improve your model? Customer indemnification for how they use outputs?

Training Data Rights

Do you train on customer inputs? Is there an opt-out mechanism? How is data anonymized? Can competitors' data train your model? This is make-or-break for enterprise deals.

Accuracy & Hallucination Disclaimers

No guarantee of accuracy. Human review requirements. Prohibited use cases (medical, legal, financial advice). Liability cap for reliance on outputs.

Input Data Processing

How long are prompts/inputs retained? Are inputs logged, and where? Confidentiality of customer prompts? Input data deletion rights?

Model Changes & Deprecation

Notice before model updates? Ability to pin to specific model version? Deprecation timeline for older models? Performance consistency guarantees?

Rate Limits & Usage

Token/request limits clearly defined? Overage pricing transparent? Throttling policies? Fair use restrictions that could catch enterprise users off guard?

Plus Standard SaaS Clauses

AI-specific provisions layer on top of these SaaS essentials

Uptime/SLA

Service availability commitments

Data Ownership

Customer data belongs to customer

Liability Caps

Limitation of damages

Indemnification

IP and third-party claims

Governing Law

Choice of law & venue

Termination

Exit rights & data return

Security

SOC 2, encryption, breach notice

Auto-Renewal

CA compliance disclosure

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Analysis Results

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