AI Product Counseling
Building AI products creates legal questions that standard tech counsel is not equipped to answer. We advise AI product teams on the specific legal risks of training data, model outputs, and deployment.
Do You Actually Need This?
AI product development creates legal exposure at every stage — these four situations mean you need specialized counsel now.
You are training a model on third-party data — scraped, licensed, or synthetic.
The legal status of training data is actively litigated in the US and Canada. Using copyrighted data, personal data, or data with contractual restrictions without appropriate rights creates infringement and privacy exposure that can attach to your model and every product built on it.
You are building a product that generates text, images, code, or decisions.
AI-generated outputs raise unresolved IP questions — who owns the output, what third-party content might be embedded in it, and what liability attaches if the output is wrong or harmful. Companies deploying generative AI need clear contractual disclosures and output IP policies before going to market.
You are integrating a third-party AI model (OpenAI, Anthropic, Google, etc.) into your product.
AI API provider agreements contain provisions that directly affect your IP, your data, and your liability — including training data restrictions, output ownership disclaimers, and indemnification limitations. Most founders sign these agreements without reading the provisions that matter most.
Your AI product operates in a regulated domain — finance, health, HR, education, or law.
Sector regulators in the US and Canada are applying existing laws to AI — the CFPB on credit decisions, HHS on health AI, the EEOC on employment AI. Operating an AI product in a regulated domain without a legal risk assessment is not a gray area — it is an enforcement target.
What You Get
- Legal Assessment
Training Data Rights Review
A legal review of your training data sources — licenses, scraping policies, user data consent, and synthetic data generation — identifying the rights you have and the gaps that need to be closed.
- Policy Document
AI Output & IP Policy
A documented policy for your AI product's output — ownership, disclosure obligations, user rights, and limitation of liability for AI-generated content — drafted for inclusion in your terms of service and customer contracts.
- Contract Review
AI Vendor Agreement Review
A review of your AI provider agreements (OpenAI, Anthropic, Google, Hugging Face, etc.) — identifying the provisions that affect your IP ownership, data rights, and liability, and negotiating where possible.
- Regulatory Memo
AI Regulatory Compliance Review
A jurisdiction-specific memo assessing your AI product's exposure under applicable law — EU AI Act, CCPA, Quebec Law 25, and sector-specific regulations — with a prioritized compliance roadmap.
Flat Fee. No Surprises.
Training Data Review
From $2,500one-time assessment- Training data source audit
- License and consent review
- Risk summary
- Remediation recommendations
- Recommended
AI Product Counsel
From $5,000full engagement- Training data + output IP review
- AI vendor agreement review
- Output policy drafting
- Regulatory exposure memo
Ongoing Advisory
From $3,000/momonthly retainer- Regulatory monitoring
- New feature legal review
- AI vendor contract support
- Priority response
Your Questions Answered
It depends on the source, the license, and your jurisdiction. The legal status of AI training on copyrighted data is actively litigated — courts in the US and Canada have not fully resolved whether training constitutes fair use or infringement. Web scraping personal data without consent also raises CCPA and PIPEDA exposure. A training data rights review before you build is far cheaper than defending a copyright claim after.
Output ownership depends on your agreement with the AI provider and applicable copyright law. OpenAI's ToS assigns output ownership to the user (subject to restrictions). US Copyright Office has held that purely AI-generated works are not copyrightable. In Canada, copyright requires human authorship. Significant human creative input into the output process strengthens ownership claims.
The EU AI Act (in force since August 2024) classifies AI systems by risk level. High-risk systems (in HR, credit, education, law enforcement) require: conformity assessments, technical documentation, human oversight, and registration in an EU database. General purpose AI models must disclose training data and comply with copyright law. Any company deploying AI to EU users is potentially subject to the Act.
AI chatbots create: (1) output liability if the chatbot gives wrong or harmful information (especially in health, legal, or financial contexts), (2) IP infringement if outputs reproduce third-party copyrighted content, (3) defamation exposure if outputs make false statements about real people, and (4) data privacy risk if the chatbot processes personal data. Each requires specific contractual and policy mitigations.
AI product legal questions — training data rights, output IP, EU AI Act compliance, AI vendor agreements — are genuinely specialized. A general tech attorney may be able to handle the underlying contract law, but the AI-specific regulatory landscape (EU AI Act, automated decision rights under CCPA and Law 25, sector-specific AI guidance) requires counsel who tracks these developments actively.
