AI Framework Checklist · Free Governance Resource

AI Framework Checklist
For Law Firms (EU & US)

A structured 12-point compliance framework for law firms deploying or using AI systems, covering EU AI Act obligations, U.S. state AI legislation, professional responsibility, and ongoing regulatory readiness.

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Full Compliance Framework

Twelve compliance domains
adapted for law firm operations

This checklist translates AI compliance requirements from the EU AI Act, U.S. state AI legislation, and professional responsibility standards into actionable controls for law firms that develop, procure, or use AI systems in legal operations, client work, and firm management.

01

Scope and applicability check

Identify every AI system your firm develops, deploys, procures, or uses, including legal research tools, document review platforms, drafting assistants, transcription services, and any AI integrated into practice management or client-facing workflows.

  • Determine whether the EU AI Act, U.S. state AI laws, or both apply to your firm based on client geography, data processing locations, and jurisdictional scope
  • Classify each system by risk level under the EU AI Act (unacceptable, high, limited, minimal risk)
  • Document jurisdictional scope and regulatory exposure for each system, including cross-border client work
02

Governance and accountability framework

Adopt a formal AI governance policy that addresses the firm's professional responsibility obligations, not just technology risk.

  • Assign a Responsible AI Lead, governance committee, or external AI governance advisor with authority to approve, restrict, or prohibit specific AI use cases
  • Maintain lifecycle documentation and audit trails covering AI tool selection, approval decisions, use-case authorization, and output review processes
  • Provide staff training on AI compliance, ethical AI use, and the firm's specific SOPs for each approved use case
03

Risk assessment and classification

Conduct periodic AI-specific risk assessments covering professional responsibility exposure, client confidentiality, privilege protection, and sanctions risk.

  • Perform Fundamental Rights Impact Assessments (FRIA) for high-risk AI systems where required by the EU AI Act or where the firm uses AI in decisions affecting individuals
  • Document risk level, mitigation plans, and residual exposure for each system
  • Reassess after major model changes, vendor updates, data changes, or new regulatory requirements
04

Data and model management

Maintain a data inventory covering all sources, processing activities, and use cases for AI-related data within the firm.

  • Ensure data quality, representativeness, and fairness in all training data, inputs, and prompt content
  • Track model lineage and version control for any AI systems the firm develops or fine-tunes
  • Implement human oversight and fallback mechanisms for every AI-assisted workflow that produces client-facing work product
05

Transparency and client rights

Disclose AI use in products and decisions affecting clients, opposing parties, courts, and regulators where required by professional responsibility rules, court orders, engagement terms, or client instructions.

  • Provide explanation and recourse mechanisms where AI-assisted analysis or recommendations are used in client-facing deliverables
  • Comply with labeling and transparency duties under EU law and applicable U.S. state legislation
  • Avoid misleading representations of AI capabilities in client communications, marketing, or RFP responses
06

Monitoring and post-deployment

Monitor AI system performance, drift, accuracy, and fairness on an ongoing basis, not only at initial deployment.

  • Implement post-market surveillance for high-risk AI systems as required by the EU AI Act
  • Maintain incident logs, response procedures, and escalation paths for AI-related quality failures, hallucination events, or data exposure incidents
  • Conduct internal or external compliance audits at defined intervals
07

Vendor and third-party oversight

Document all external LLM models, plugins, APIs, datasets, and third-party services used by the firm or integrated into firm systems.

  • Include compliance warranties, data handling commitments, audit clauses, and incident notification requirements in vendor contracts
  • Review third-party risk, data residency, sub-processor chains, and dependency exposure on a regular schedule
  • Verify that vendor LLM models and tools meet ABA and applicable bar association confidentiality and competence standards
08

Privacy and cybersecurity

Ensure GDPR and U.S. privacy law compliance in all AI-related data processing, including prompt content, client data, and model outputs.

  • Apply appropriate security measures: encryption at rest and in transit, access control, logging, and prompt anonymization where client data is involved
  • Conduct Data Protection Impact Assessments (DPIA) where required by GDPR or where AI processing involves sensitive client data, privileged information, or high-volume personal data
09

Documentation and records

Maintain an AI Compliance File for each AI system the firm uses, covering the full lifecycle from procurement or development through deployment, monitoring, and retirement.

  • Include data lineage, design logs, model cards, testing results, approval records, and review documentation
  • Be audit-ready with organized evidence of compliance that can be produced for clients, courts, bar authorities, regulators, or insurers
10

Training and culture

Train both technical and legal staff on AI compliance obligations, firm-specific SOPs, and professional responsibility requirements applicable to AI-assisted work.

  • Promote internal awareness of ethical AI practices, hallucination risks, citation verification, and output review standards
  • Integrate governance reviews into the firm's product launch, tool procurement, and matter opening cycles
11

Ongoing regulatory monitoring

Track EU AI Act guidance, enforcement actions, and U.S. state AI legislation on an ongoing basis, not as a one-time exercise.

  • Update internal policies, SOPs, and vendor requirements as new rules are introduced or existing rules are amended
  • Designate a compliance monitor, internal champion, or external advisor responsible for regulatory tracking and policy updates
12

Incident response and escalation

Define incident classification, reporting thresholds, and escalation procedures for AI-related failures, data exposure events, hallucination incidents, and compliance breaches.

  • Notify affected clients, stakeholders, bar authorities, and regulators promptly where required by law, engagement terms, or professional responsibility obligations
  • Review insurance coverage for AI-related liabilities, including malpractice, cyber liability, and professional indemnity policies

This compliance checklist is not a substitute for a firm-specific AI governance framework or independent legal advice. It is a structured starting point for law firm leadership that needs to move from informal AI usage to controlled, documented, and defensible AI compliance across both EU and U.S. regulatory frameworks.

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