Why Do AI SaaS Contracts Require Special Provisions?
Software-as-a-Service agreements for AI platforms like ChatGPT, Claude, Gemini, or specialized AI tools create unique contractual considerations beyond traditional SaaS. AI SaaS involves processing customer data for training or inference, delivering probabilistic outputs with variable accuracy, evolving capabilities through continuous model updates, and unclear intellectual property rights in inputs and outputs.
Poorly drafted AI SaaS agreements create significant risks including ambiguous rights in customer data and AI outputs, inadequate service level commitments for AI performance, insufficient liability protections for AI errors, and regulatory compliance gaps for privacy and AI regulations.
For AI providers, well-structured agreements limit liability while enabling business. For customers, comprehensive terms ensure service quality and protect valuable data and workflows. Understanding essential AI SaaS contract provisions helps both providers and customers negotiate balanced agreements managing risks while enabling innovation.
Scope of Services and Use Rights
Service Description
Clearly describe AI services provided including specific models or capabilities available, usage-based or subscription-based access, applicable usage limits or quotas, and API access or UI-based interaction.
Ambiguous service descriptions create disputes about what providers must deliver.
Acceptable Use Policies
AI SaaS agreements should include acceptable use policies prohibiting uses such as generating illegal content or facilitating crimes, training competing AI models, circumventing usage limits or security measures, and violating third-party intellectual property rights.
Violations justify service termination.
User Accounts and Access Control
Address account management through designation of authorized users, authentication and security requirements, restrictions on account sharing or resale, and customer responsibility for user conduct.
Data Rights and Usage
Customer Data Ownership
Clarify that customers retain ownership of data they provide including input data submitted to AI services and any resulting outputs generated.
Providers should not claim ownership of customer content.
Provider Use of Customer Data
Specify whether and how providers may use customer data. Critical distinctions include whether data is used to train or improve AI models generally, processed only for providing services to specific customers, aggregated or anonymized for analytics, or retained after service termination.
Customers often require commitments that their data won’t train public models.
Data Processing Agreements
For AI processing personal data, incorporate Data Processing Agreements meeting GDPR requirements covering processor obligations, sub-processor management, data security measures, and assistance with data subject requests.
Intellectual Property Rights
Ownership of AI Outputs
Address ownership of AI-generated content. Typical approaches include customer ownership of outputs generated from their inputs, provider ownership with license to customer, or shared ownership with specified rights.
Given uncertainty around AI-generated content copyrightability, providers often grant licenses rather than asserting ownership.
Pre-Existing IP
Agreements should clarify that customers retain rights in pre-existing intellectual property, providers retain rights in underlying AI technology and models, and neither party gains rights in the other’s pre-existing IP except as expressly licensed.
Feedback and Improvements
Providers typically request broad rights to feedback from customers about AI service improvements including unlimited rights to use feedback for enhancements, no compensation for customer suggestions, and no confidentiality obligations regarding feedback.
Customers should ensure feedback doesn’t include confidential information.
Service Level Agreements
Availability and Uptime
SLAs should specify minimum availability percentages (e.g., 99.9% uptime), measurement methodologies excluding scheduled maintenance, and remedies for failures like service credits.
AI services face unique availability challenges due to model training interruptions and infrastructure requirements.
Performance Metrics
For AI, performance SLAs might include response time for API calls or UI interactions, throughput for batch processing, and accuracy or quality metrics where feasible.
However, guaranteeing AI output accuracy is difficult given probabilistic nature.
Service Credits
SLAs typically provide service credits as exclusive remedies for availability failures specifying credit amounts based on downtime percentage, claim procedures and timelines, and caps on total credits (often not exceeding fees paid).
Limitations and Exclusions
SLAs include exclusions for downtime caused by factors outside provider control such as customer misuse or modifications, third-party services or infrastructure, force majeure events, or scheduled maintenance.
Warranties and Disclaimers
Provider Warranties
AI providers typically warrant that they have rights to provide services, services will substantially conform to documentation, and they’ll use industry-standard security measures.
However, providers disclaim warranties about AI accuracy, suitability for specific purposes, and error-free operation.
Disclaimer of Implied Warranties
Providers disclaim implied warranties of merchantability and fitness for particular purpose, stating that AI services are provided “as is” except for express warranties.
These disclaimers are enforceable in commercial contexts but may not protect against all liability.
Customer Responsibilities
Agreements allocate responsibilities to customers including evaluating AI suitability for their uses, implementing human oversight where needed, and complying with applicable laws in their use of AI.
Limitation of Liability
Liability Caps
AI SaaS agreements typically cap provider liability at amounts such as fees paid by customer in prior 12 months or specified dollar amounts.
Caps don’t apply to certain liabilities like intellectual property infringement or willful misconduct.
Exclusion of Consequential Damages
Providers exclude liability for indirect, incidental, consequential, or punitive damages including lost profits, lost data, business interruption, or reputational harm.
Customer-Favorable Modifications
Enterprise customers may negotiate higher liability caps, narrower exclusions for critical failures, or separate provisions for data breaches or security incidents.
Confidentiality and Security
Confidential Information
Define confidential information including customer data and business information, provider’s AI technology and methodologies, and terms of agreement itself.
Specify use restrictions, protection obligations, and exceptions like publicly available information or independently developed information.
Security Obligations
Providers should commit to implementing appropriate administrative, technical, and physical security controls, regular security assessments and testing, encryption for data in transit and at rest, and incident response procedures.
Security Incidents and Breaches
Agreements should require prompt notification of security incidents affecting customer data, cooperation in investigation and remediation, and compliance with breach notification laws.
Compliance and Regulatory Obligations
Privacy Law Compliance
Address compliance with GDPR, CCPA, and other privacy laws through incorporation of Data Processing Agreements, commitments to process data lawfully, and assistance with privacy obligations like data subject access requests.
Industry-Specific Regulations
For AI in regulated industries, address compliance with healthcare regulations like HIPAA, financial services requirements, or sector-specific AI regulations emerging under EU AI Act or similar frameworks.
Export Control Compliance
For AI with advanced capabilities or international deployments, address export control obligations including technology classification and licensing, restrictions on use in certain countries, and customer screening requirements.
Indemnification
Provider Indemnification
Providers typically indemnify customers for third-party claims that AI services infringe intellectual property rights, subject to limitations and exclusions.
Providers don’t indemnify for infringement arising from customer misuse or modifications.
Customer Indemnification
Customers indemnify providers for claims arising from customer data violating laws or third-party rights, customer’s use of services violating agreement terms, or customer’s combination of AI services with other technologies.
Indemnification Procedures
Indemnification provisions specify claim notification requirements, control of defense, cooperation obligations, and settlement approval rights.
Term and Termination
Subscription Terms
Specify initial term and renewal provisions including automatic renewal unless canceled, early termination rights and fees, and notice periods for cancellation.
Termination for Cause
Either party may terminate for material breach if not cured within specified period, insolvency or bankruptcy, or violations of acceptable use policies.
Effect of Termination
Upon termination, customers lose access to AI services, providers must return or delete customer data per instructions (subject to retention requirements), and customers pay fees for services through termination.
Survival provisions ensure certain terms like confidentiality and liability limitations continue post-termination.
Audit Rights
Compliance Audits
Customers may request audit rights to verify provider compliance with security, privacy, or contractual obligations through on-site audits or documentation review, third-party assessments or certifications, and reasonable frequency limitations.
SOC 2 and Certifications
Many providers satisfy audit requirements by obtaining and sharing SOC 2 Type II reports, ISO 27001 certifications, or other third-party attestations rather than allowing customer-specific audits.
Dispute Resolution
Governing Law
Specify governing law for agreement interpretation and disputes. For international agreements, choice of law significantly impacts rights and remedies.
Arbitration vs. Litigation
Many AI SaaS agreements require arbitration for disputes providing faster, private resolution, specialized arbitrators, and limited appeal rights.
However, arbitration may disadvantage smaller customers lacking resources.
Venue and Jurisdiction
For agreements permitting litigation, specify exclusive venue and jurisdiction for disputes. Providers typically choose their home jurisdiction while customers seek their own.
Special Provisions for Enterprise Customers
Custom Pricing and Terms
Enterprise agreements often include volume-based pricing, committed spend discounts, or custom service levels beyond standard offerings.
Integration and Support
Enterprise SLAs may guarantee dedicated support teams, technical integration assistance, and custom feature development.
Exit Assistance
Large customers may negotiate exit assistance provisions ensuring data export in usable formats, transition periods for migration, and cooperation with replacement vendors.
Modification and Updates
Service Updates
Providers reserve rights to update AI models and services. Agreements should address whether customers can lock to specific model versions, notification requirements for significant changes, and customer testing periods before mandatory updates.
Terms of Service Changes
Providers typically reserve rights to modify terms with notice. Customers should negotiate that material adverse changes allow termination rights or require consent for existing customers.
Conclusion: Comprehensive AI SaaS Contracting
AI SaaS agreements require careful attention to unique AI considerations beyond standard SaaS terms. Essential provisions include clear data rights and usage restrictions, appropriate service levels and performance commitments, intellectual property allocations for inputs and outputs, comprehensive security and privacy protections, and balanced liability allocation.
Both providers and customers benefit from addressing AI-specific issues proactively in contracts, reducing disputes and creating clear expectations for innovative services.
Contact Rock LAW PLLC for AI SaaS Contract Counsel
At Rock LAW PLLC, we help AI companies and customers negotiate comprehensive SaaS agreements.
We assist with:
- AI SaaS agreement drafting and negotiation
- Terms of service and acceptable use policies
- Data processing agreements and privacy compliance
- Service level agreement structuring
- Intellectual property provisions for AI outputs
- Contract review and risk assessment
Contact us for expert guidance on AI SaaS contracting.
Related Articles:
- Warranties in AI Software Contracts
- Data Processing Agreements for AI Companies
- Terms of Service for AI API Providers
Rock LAW PLLC
Business Focused. Intellectual Property Driven.
www.rock.law/