Artificial Intelligence
Artificial Intelligence — Legal Services
Practical legal guidance for organisations that develop, deploy or procure AI systems. We focus on regulatory compliance, data protection, intellectual property, governance and contract risk for AI projects across multiple jurisdictions.
See also: Financial services, Foreign direct investment, Tax
Overview
AI projects raise mixed legal issues: regulatory requirements for high‑risk systems, data processing and consent, IP ownership for models and outputs, contractual allocation of liability, and sector-specific rules (healthcare, finance, transport). This page summarises core topics and practical steps an organisation should take to manage legal risk when using AI.Related pages: About TRW · Practice areas
Key services
Regulatory compliance
Regulatory review and compliance planning for AI-specific rules and cross‑border obligations, including preparation for conformity assessments and regulator engagement. See servicesGenerative AI & LLMs
Advice on training‑data rights, licensing terms for models, model governance, content ownership and practical controls around generated outputs.Data protection
Assessment of personal data processing in model training and operation, DPIAs (data protection impact assessments), consent mechanisms and international transfers.Intellectual property
IP strategy for models, datasets and outputs; licensing models, trade secret protection and open source compliance.Governance & ethics
Designing internal governance, risk frameworks, bias testing and explainability measures to meet policy and stakeholder expectations.Liability & dispute preparation
Contract drafting to allocate responsibilities, insurance review and defence strategy for disputes arising from automated decision‑making and algorithmic harms.How we work with clients
- Intake & technical review. We map stakeholders, data flows and the model architecture.
- Risk assessment. Identify regulatory, data, IP and contractual risks; produce a concise legal risk memo.
- Roadmap & controls. Draft compliance actions, governance steps, DPIAs and contractual templates.
- Implementation support. Review policies, contracts, vendor terms and assist with regulator liaison where needed.
- Ongoing monitoring. Periodic reviews, audit support and incident response planning.
Practical checklist (starter)
- Document data sources used for training and processing.
- Run an initial Data Protection Impact Assessment (DPIA) where personal data is involved.
- Clarify ownership and licence terms for models, datasets and outputs.
- Define performance and bias testing procedures and thresholds.
- Draft end‑user and vendor contracts that allocate responsibility for model outputs.
- Set incident reporting lines and a retention policy for audit trails.
Frequently asked questions
When should an organisation carry out a DPIA for an AI system?
A DPIA is appropriate when processing is likely to result in high risk to individuals’ rights — for example, profiling, automated decision‑making with legal or similarly significant effects, or large‑scale processing of sensitive data. Early assessment helps set technical and contractual controls.
Who owns model outputs?
Ownership depends on contracts, contributor agreements and the law in the relevant jurisdiction. It is best addressed contractually: specify rights in training data, models, and generated outputs to avoid ambiguity.
How can bias be managed in deployed models?
Bias management combines governance, technical testing, representative data, and documented mitigation steps. Regular monitoring, clear incident processes and stakeholder communication are part of a defensible approach.
What contractual steps reduce supplier risk?
Include warranties about data rights, security obligations, audit and reporting rights, notice requirements for incidents, liability caps where appropriate, and clear SLAs for model updates/maintenance.
How do cross‑border data transfers affect model training?
Cross‑border transfers may trigger data protection restrictions. Use lawful transfer mechanisms (standard contractual clauses, adequacy decisions) and minimise transfers by using pseudonymisation or localised training where feasible.
Can TRW assist with regulator engagement?
Yes — we prepare briefing materials, compliance evidence and can accompany client engagement with regulators. For regulatory strategy, see our practices.
Contact
For a focused discussion on your AI programme, choose one of the options below.More practice pages: Arbitration · Employment · Supreme Court listings