BUYER GUIDE · UPDATED AUGUST 20, 2026
AI Governance Framework for Corporate Boards
A practical board AI governance framework covering materiality, ownership, evidence, risk tiers, human control, reporting, and incidents.
Start with materiality
Boards do not need an inventory of every productivity tool. They need visibility into AI that affects customers, revenue, safety, employment, regulated decisions, financial reporting, intellectual property, security, and strategic dependency.
Assign decision rights and evidence
Every material system needs an executive owner, intended use, known limitations, approval authority, monitoring plan, human intervention, vendor obligations, and a record of why deployment was considered acceptable.
Use risk tiers to match oversight
Low-consequence assistance should not receive the same process as a consequential customer or financial decision. Risk tiers should change testing, approval, monitoring, disclosure, human control, and board reporting requirements.
Review incidents and near misses
Governance improves when exceptions, overrides, drift, and failed assumptions are reviewed. A board should understand whether the control system detected the issue, whether people acted, and what changed afterward.
Operating evidence
The principal case documents how the AGI Brazil operation scaled from approximately $35M to more than $150M through coordinated commercial organization, channels, cadence, and P&L priorities. Additional KPI evidence remains withheld until authorized.
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