Big Data Use and Licensing Agreements: Key Provisions, Privacy-Enhancing Technologies, Risk Mitigation Strategies

Companies are increasingly exploiting massive amounts of consumer information from social networking sites, online interactions, connected devices, and other sources—collectively known as big data—to generate revenue and train artificial intelligence models. Businesses considering using big data should evaluate whether to anonymize or pseudonymize data, what due diligence to perform, and how privacy‑enhancing technologies can minimize compliance and litigation risks.

Carefully negotiated licensing agreements specific to big data will maximize the right to use, access, and analyze data while minimizing liability exposure.

Traditional licenses are often ineffective in addressing the unique issues big data presents, including re‑identification risks, evolving privacy regulations, and the growing use of data in AI/ML.

Big data licensing agreements should include provisions addressing warranties, indemnification, limitation of liability, privacy and data security, confidentiality, and audit rights, as well as considerations for downstream use in AI training and model outputs. By understanding the critical clauses to include in big data licenses and the common pitfalls to avoid, counsel can effectively draft and negotiate agreements in their clients' best interests.

Listen as our authoritative panel discusses what big data is and the practical and legal considerations surrounding its use. The panel will also discuss best practices for drafting high priority clauses in big data licenses.

I. Introduction: big data in today's landscape

A. Definitions and key data types

II. Legal and regulatory developments

A. GDPR, CCPA/CPRA, and other U.S. state laws

B. Data subject rights, consent management, cross-border, and localization

III. Privacy-enhancing technologies

A. Differential privacy, tokenization, synthetic data

B. De-identification vs. pseudonymization

IV. Key contractual provisions in big data licenses

A. License and use restrictions (e.g., AI training)

B. Warranties, representations, and disclaimers

C. Indemnification and limitations of liability

D. Confidentiality, data ownership, and sub-licensing rights

V. Big data in AI/ML: new risks and responsibilities

A. Licensing for training datasets vs. outputs

B. Legal concerns around bias, explainability, and model misuse

VI. Compliance, oversight, and enforcement

A. Audit rights and monitoring obligations

B. Documentation, due diligence, and vendor management

C. Enforcement trends and litigation

The panel will review these and other relevant issues:

• Key legal and contractual risks in obtaining and using big data
• Drafting license agreements for use in AI/ML models
• Regulatory impacts from GDPR, CCPA/CPRA, and state laws
• Strategies for anonymization, pseudonymization, and other privacy enhancements
• Contract downstream liability issues
• Audit, indemnity, and data security provisions to reduce exposure