Current state and objectives
Assess organisational goals, use cases, tools, vendors, data and management foundations.
AI LEGAL SERVICE
Enterprise AI Development and Governance
Establish enterprise AI planning, tool admission, data permissions, internal policies, training, audit and incident response.
SERVICE OVERVIEW
Objectives and scope of service
This service supports organisations introducing AI tools at scale, building internal knowledge systems or developing AI-enabled workplaces. It establishes governance across inventories, responsibilities, risk tiers, procurement, permissions, workforce use, training, audit and incident response.
REVIEW SCOPE
Six connected review areas
Governance structure
Define management, business, technical, legal, security, procurement and audit responsibilities.
Risk tiering and admission
Create proportionate evaluation, procurement, testing, approval and exit procedures.
Data and permission management
Define permitted materials, restricted inputs, knowledge access and approval for sensitive actions.
Policy and process integration
Integrate AI governance with procurement, security, data, release, vendor and incident processes.
Training, audit and improvement
Deliver role-based training and establish execution checks, reporting, audit and policy updates.
DELIVERABLES
Outputs for decision and implementation
- 01Enterprise AI development and governance plan
- 02AI application, model and vendor inventory
- 03Responsibility matrix and risk-tiering standard
- 04Procurement, use and incident-response policies
- 05Role guidance, training materials and audit checklist
STARTER MATERIALS
Materials for an efficient start
- 01Organisation structure and business plan
- 02AI application, model and vendor inventory
- 03Use cases and system architecture
- 04Data, procurement, security and audit policies
- 05Approval processes and permission settings
- 06Usage records, complaints and incident materials
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
When should enterprise AI governance begin?＋
It is advisable to begin when an organisation plans scaled procurement, internal knowledge systems or cross-department deployment.
How does this differ from model and platform governance?＋
Enterprise AI governance focuses on internal adoption, policies and workforce use. Model and platform governance focuses on product and platform responsibility when capabilities are provided or operated externally.
Can this integrate with existing security and data policies?＋
Yes. The framework can be embedded into procurement, data protection, security, audit and vendor management.
Research
Related cases and rules
Consider the relevant cases and rules in the project’s target markets.
Legal research · United States
NIST AI Risk Management Framework
The framework organises AI risk work around Govern, Map, Measure and Manage and can support product development, procurement, deployment and continuing monitoring.
Read analysis →Legal research · ChinaChina: AI Safety Governance Framework
The framework supports graded risk identification and treatment across models, data, systems, networks, ethics and applications for AI development, deployment and use.
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.