L-G

DAT-01

Data Governance Framework Template

Establishes the foundational data governance policies for legal AI, covering classification, vendor data protection, Shadow AI governance, regulatory compliance, and Agentic Tier data provisions.

ModuleoperationalAnnualAdoption lensDefensibility lens

Audience

GC / CLOLegal Operations

3–6 weeks for initial framework; 1–2 weeks for annual review and updates

Executive Summary

This module provides a complete Data Governance Framework for legal departments implementing AI. It defines a four-level data classification model, AI-specific handling rules, and mandatory vendor data protection requirements aligned with VEN-04 and DAT-03. It embeds Risk Taxonomy 2026 across nine classes, with upgraded Class 6 Shadow AI governance, immediate STR-07 escalation rules, and GOV-03 Risk Register integration. The framework integrates the AI Bill of Materials (AI BoM) as the canonical scope for data governance and monitoring, and introduces five mandatory Agentic Tier Data Provisions for Level 4 (AI as Executor) tools. It maps controls to ABA Model Rules, GDPR, EU AI Act, and key US state privacy laws, and specifies DPS-grade evidence retention for defensibility. Use this module to design, implement, and maintain a defensible, audit-ready data governance regime for legal AI, from blueprint through ongoing monitoring and incident response.

Metric 0 Pre-Check

Before establishing or updating the data governance framework, confirm all five gates are satisfied.

| Gate | Check | Status |

|—|—|—|

| M0.1 — GOV-02 Alignment | AI Use Policy (GOV-02) is current; data governance framework aligns with policy provisions | Confirm |

| M0.2 — GOV-03 Alignment | Risk Register (GOV-03) is current; data-related risk entries are up to date | Confirm |

| M0.3 — AI BoM Currency | AI BoM is available; all deployed AI tools have entries for data governance scoping | Confirm |

| M0.4 — STR-07 Authorisation | AI Task Force has reviewed the governance framework scope; high-risk classifications confirmed | Confirm |

| M0.5 — VEN-04 Alignment | VEN-04 Security and Compliance Checklist provisions are reflected in Vendor Data Protection section | Confirm |

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Purpose

This Data Governance Framework establishes policies and procedures for the secure, ethical, and compliant use of data in AI applications within the Legal Department. It ensures AI initiatives enhance legal service delivery while maintaining the highest standards of client confidentiality, professional responsibility, and regulatory compliance.

Defensibility Evidence

Signed framework and amendments, data classification records, vendor DPAs, Class 6 Shadow AI incident records, Agentic Tier data provision assessments, data breach response records, and AI BoM data governance scope records are DPS Defensibility lens evidence demonstrating systematic, governed data management for legal AI. Retained for 5 years (training records, STR-07 briefings) and 7 years (framework, DPAs, incident records, breach response).

Operational Artefacts

DAT-01 Data Governance Framework Template (Policy Document)
docx · v2026.1
Gated
DAT-01 Data Governance Implementation Checklist
checklist · v2026.1
Gated
DAT-01 DPS Evidence Register for Data Governance
xlsx · v2026.1
Gated

Framework Crosswalk

NIST AI Risk Management Framework

NIST

Aligns data governance, monitoring, and incident response controls with NIST AI RMF functions (Map, Measure, Manage, Govern).

EU AI Act

European Union

Maps AI BoM, risk classification, data governance, and high-risk controls to EU AI Act obligations, including registration and oversight.

GDPR

European Union

Implements GDPR principles of processing, DPIA requirements, and data subject rights for AI-related processing.

ABA Model Rules of Professional Conduct

American Bar Association

Connects AI data governance to Rules 1.1, 1.6, and 5.3 on competence, confidentiality, and supervision.

Operational Details

Inputs

· Current AI Use Policy (GOV-02)
· Risk Register with data-related entries (GOV-03)
· AI Bill of Materials (AI BoM) with all deployed AI tools
· DAT-02 Data Inventory and Classification Matrix
· VEN-04 Security and Compliance Checklist
· DAT-03 Vendor DPA Checklist
· Applicable regulatory requirements (ABA Model Rules, GDPR, EU AI Act, US state privacy laws)
· Existing enterprise data governance and privacy policies

Outputs

· Approved Data Governance Framework for legal AI
· Documented four-level data classification scheme and handling rules
· Completed vendor DPAs and VEN-04-aligned safeguards for AI vendors
· Shadow AI (Class 6) governance policy and escalation procedures
· Agentic Tier Data Provisions assessment records for Level 4 tools
· Updated AI BoM with data governance scope annotations
· GOV-03 Risk Register entries for data and Class 6 incidents
· DPS Defensibility evidence pack for data governance and incidents

Owner

General Counsel + Legal Operations + Data Protection Officer

Telemetry & Observability

Telemetry-ready

Key Takeaways

Define and enforce a four-level data classification scheme tailored to legal AI workloads.
Use the AI BoM as the authoritative scope for all AI-related data governance and monitoring.
Apply strict vendor data protection controls, including no-training clauses and DPAs, before any data access.
Treat Shadow AI as Risk Taxonomy 2026 Class 6 with immediate STR-07 escalation and GOV-03 logging.
Implement the five Agentic Tier Data Provisions before allowing Level 4 tools to touch Level 3–4 data.
Map data governance controls to ABA Model Rules, GDPR, EU AI Act, and US state privacy laws.
Retain framework artefacts as DPS Defensibility evidence to withstand regulatory and client scrutiny.

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Module Details

Type

Pillar

Layer

G · Governance

Duration

3–6 weeks for initial framework; 1–2 weeks for annual review and updates

Advisory

Yes

Access

Member access

Certification

Practitioner

Maturity Bands

FoundationalOperationalIntegratedOptimisedDefensible

Risk Classes Mitigated

Available Through

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Governance

Methodology: v2026.1
Last reviewed: 23 May 2026
Verified: 23 May 2026

ADVISORY

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