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The operational capability layer of the Legal AI OS.
Modules are the institutional artefacts a legal function runs to advance maturity, produce Defensibility evidence, and operate on canonical ground in front of a regulator or a board. Anchored across the 8 Pillars and 6 Operating Layers. Methodology-versioned. Editorially independent.
PILLAR
AUDIENCE
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28 Modules
BUS-01
Business Case and Cost of Inaction
The foundational investment approval instrument that quantifies legal AI's cost of inaction, builds CFO-grade ROAI projections, and authorises the governance and measurement machinery.
Module
2–4 weeks for first full build; 1–2 days for annual refresh
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CHG-01
Change Management Architecture
5-step change management framework for human-centred legal AI adoption and cultural transformation
Module
18-week initial rollout; quarterly reinforcement and annual refresh aligned with SUS-05.
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CLI-01
Client Disclosure and Consent Guidelines
Client disclosure and informed consent framework for transparent AI use in legal engagements
Module
1–2 hours per new matter; 30 minutes per material AI change
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COM-01
Sponsorship Communication Plan
Stakeholder communication framework for legal AI transformation sponsorship and change management
Module
Initial design 1–2 weeks; 2–4 hours per month for ongoing execution and review.
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COT-01
Continuous Optimization Cycle
Systematically capture AI performance feedback, map signals to Risk Taxonomy 2026 classes, and execute ROAI-attributed optimization cycles across the legal department's AI portfolio.
Module
Initial setup 2–4 weeks; continuous telemetry; monthly analysis; quarterly planning and review (0.5–1 day per quarter).
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DAT-02
Data Inventory & Classification Methodology
Classify every data asset by sensitivity level, assign AI processing permissions by classification, and build the governance record that proves Defensible AI adoption.
Module
Initial build 4–6 weeks; quarterly updates 1–2 days; annual review 3–5 days
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DAT-03
Vendor Data Protection Obligations
Canonical checklist for reviewing and negotiating AI vendor data protection agreements.
Module
3–6 hours per vendor engagement, depending on complexity and negotiation cycles
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DAT-04
Data Minimization Methodology
Apply data minimization across every stage of the AI data lifecycle, govern shadow AI through the canonical Class 6 protocol, and build the evidence record that proves Defensible AI.
Module
Initial rollout 4–6 weeks; continuous monitoring with monthly and quarterly checkpoints
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GOV-01
Defensible AI Governance Framework
Establish the governance structure, policy suite, and risk register that make Legal AI defensible to boards and regulators.
Module
2–4 weeks first run; 1 day annual review
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GOV-02
AI Use Policy
Define what AI use is permitted, prohibited, and supervised across the legal department — the operational policy that makes AI governance real.
Module
Initial deployment 2–4 weeks; 1 day for annual review
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GOV-04
Bias Testing & Monitoring Methodology
Pre-deployment bias test and continuous fairness monitoring checklist for legal AI systems
Module
Pre-deployment testing: 2–4 weeks per AI system; continuous monitoring: ongoing; quarterly audit: 1–2 days
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INS-01
AI Liability & Insurance Posture
Assess professional liability exposure, insurance coverage gaps, and vendor indemnification adequacy for AI tools across the Risk Taxonomy 2026 nine-class framework.
Module
1–2 days initial per tool; 2–4 hours per tool at renewal or quarterly review
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Advisory
The full operating system in one Programme.
Programme Design and Strategic Retainer engagements operate the canonical Module sequence end-to-end — Defensibility evidence produced, Maturity progression evidenced quarterly, methodology version pinned. The Module Library is the artefact; the engagement is the operating posture.
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