Transaction structure
Define development, purchase, subscription, licence and data relationships.
AI LEGAL SERVICE
AI Contracts and Dispute Resolution
Support procurement, development, licensing, investment and disputes involving technology, data and outputs.
SERVICE OVERVIEW
Objectives and scope of service
AI transactions combine performance, data rights, model dependencies and continuing service. Contracts should convert architecture into acceptance, rights, responsibility and exit terms; disputes require prompt preservation of versions, logs and technical evidence.
REVIEW SCOPE
Six connected review areas
Technology and acceptance
Turn performance, interface, security and service levels into tests.
Rights allocation
Allocate models, code, data, prompts, configuration and outputs.
Risk allocation
Design warranties, indemnities, limits, insurance and claims handling.
Evidence preservation
Preserve contracts, configurations, prompts, logs, outputs and communications.
Dispute strategy
Align technical facts, loss pathways and commercial objectives.
DELIVERABLES
Outputs for decision and implementation
- 01Transaction and risk map
- 02Drafted or negotiated agreement
- 03Acceptance and service-level schedule
- 04Evidence plan and chronology
- 05Dispute assessment and strategy
STARTER MATERIALS
Materials for an efficient start
- 01Commercial proposal and background
- 02Technical requirements
- 03Contracts and correspondence
- 04Delivery, test and acceptance records
- 05Logs and version information
- 06Loss evidence and third-party claims
WORKFLOW
A review process with clear hand-offs
View workflow
Define
Confirm business objectives, system boundaries and review priorities.
Map
Map data, models, people, permissions, contracts and system actions.
Assess
Review materials, interview key roles and test representative scenarios.
Remediate
Prioritise controls, documents, product changes and responsible owners.
Verify
Review changes, record the version and set reassessment triggers.
FAQ
Questions about this service
What is often missed in AI contracts?＋
Common gaps include data use, model changes, output rights, continuity, portability, exit support and technical evidence.
What should happen first in a dispute?＋
Preserve contracts, settings, versions, prompts, logs, outputs and communications before key data is overwritten.
Can lawyers help design technical acceptance?＋
Yes. Product, engineering and procurement teams can convert technical metrics into verifiable conditions and remedies.
Research
Related cases and rules
Consider the relevant cases and rules in the project’s target markets.
Case study · China
Beijing AI Text-to-Image Case
The court found the disputed image reflected the user’s intellectual input and individual expression, considering prompts, parameter adjustments and the generation process. Protection depended on the specific human contribution in this case; the decision does not make every AI-generated image copyrightable.
Read case →Case study · United StatesUS Thaler Copyright Case
The applicant named an AI system as the sole author. The appellate court upheld refusal under the human-authorship requirement of the Copyright Act of 1976, and the Supreme Court later denied certiorari. The case did not decide copyrightability of AI-assisted work with substantial human authorship.
Read case →Legal research · European UnionEU Product Liability Directive
The revised Directive brings software and AI systems within the product-liability framework and updates defect, responsible-party, evidence-disclosure and causation rules.
Read analysis →Legal research · United States Federal GovernmentUS OMB AI Governance Memoranda
OMB memoranda M-25-21 and M-25-22 govern federal-agency AI use and procurement, including accountability, high-impact uses, risk practices and contract terms.
Read analysis →RELATED SERVICES
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SPECIALIZED ENQUIRY
Initiate Your Project Scoping
Share your product stage, system capabilities, data flows, and priority legal requirements. Our practice team will confirm the scope of engagement.