Legal Counsel for AI & Machine Learning Companies
Structuring AI innovation responsibly with counsel who understands your technology.
Why AI Companies Need Focused Counsel
AI regulation is changing fast. New requirements are emerging at federal, state, and international levels, while enterprise customers are demanding stronger governance and accountability. We help you build data governance and model deployment practices that will hold up as the rules evolve, without slowing you down in the meantime.
We understand the technical realities of AI development, from training data provenance to model deployment considerations. This lets us provide practical guidance that actually works for how AI systems are built, not theoretical compliance frameworks disconnected from engineering reality.
How We Help AI Companies
Data Governance
Build data practices that support both innovation and compliance.
- Training data licensing and rights
- Data provenance documentation
- Privacy compliance (GDPR, CCPA)
Regulatory Compliance
Navigate emerging AI regulations without halting innovation.
- EU AI Act compliance planning
- State AI law compliance (Colorado, etc.)
- Sector-specific requirements (healthcare, finance)
AI Governance Frameworks
Build governance that satisfies enterprise customers and regulators.
- Responsible AI policies and procedures
- Bias testing and documentation
- Human oversight requirements
IP & Commercial
Protect your innovations and structure commercial relationships.
- Model and algorithm IP protection
- Data licensing agreements
- Enterprise AI deployment agreements
Frequently Asked Questions
What are the legal requirements for AI companies?
AI companies face evolving legal requirements including data privacy regulations (GDPR, CCPA), emerging AI-specific regulations (EU AI Act, state laws), intellectual property considerations, algorithmic accountability requirements, sector-specific regulations, and export controls. Our regulatory compliance services help you navigate this landscape.
How do AI startups protect their intellectual property?
AI startups protect IP through patents (where applicable), trade secrets for training data and model weights, copyrights for code, and contractual protections through NDAs and data licensing. The right mix depends on your technology and business model. See our IP strategy services for more.
What is AI governance and why does it matter?
AI governance encompasses the policies, processes, and controls ensuring AI systems are developed responsibly. This includes data governance, model development practices, deployment controls, and documentation. Strong governance is increasingly required by regulations, expected by enterprise customers, and essential for managing risk.
What data licensing issues do AI companies face?
AI companies face complex data licensing issues including: rights to use data for training, restrictions on commercial use, requirements to delete or modify models, chain-of-custody issues, user-generated content considerations, and synthetic data ownership. These issues affect both training and deployment rights.
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