AI Governance for Family Offices
A family office AI policy becomes useful only when it assigns decisions, access, review, and incident responsibilities to named roles.
Photo: MINEIA MARTINS / Pexels
Family office AI governance is the set of policies, roles, technical controls, and review practices that determine which AI uses are allowed, what information may be processed, who can approve consequential actions, and how incidents or vendor changes are handled.
A policy without owners is only advice.
Family offices bring together principals, employees, investment teams, outside counsel, tax advisers, household staff, and technology vendors. A generic employee policy does not account for those different duties and access patterns.
Start with a small governance group. The family or its delegate sets risk appetite. An executive owner decides which uses move forward. Technology and security owners implement access and monitoring. Counsel reviews privacy, contractual, fiduciary, and jurisdictional questions. Business owners remain accountable for the work produced with AI.
NIST organizes AI risk work around four functions: Govern, Map, Measure, and Manage. A family office can use that sequence without turning governance into a large bureaucracy.
Seven domains cover the decisions that matter.
| Domain | Required decision | Evidence to keep |
|---|---|---|
| 1. Policy and accountability | Who approves use cases, exceptions, and changes? | Policy, role assignments, decision record, exception log. |
| 2. Data rules | Which information may enter each tool or model? | Data classes, source register, retention rules, prohibited-data list. |
| 3. Identity and access | Which principals, staff, advisers, and vendors can reach which data and functions? | Role matrix, access reviews, joiner and leaver records. |
| 4. Models and vendors | Which providers are approved, and under what contractual and technical conditions? | Diligence record, data-flow map, terms, evaluation results, exit plan. |
| 5. Agents and actions | What may an agent read, draft, recommend, or change? Which steps need approval? | Tool permissions, approval gates, action logs, rollback procedure. |
| 6. Monitoring and incidents | What is logged, reviewed, escalated, contained, and reported? | Audit logs, review schedule, incident plan, exercise results. |
| 7. Continuity and succession | How will the office change providers, recover service, and transfer operating knowledge? | Backups, export test, architecture record, successor access process. |
Apply more control as the consequence rises.
Low consequence
Examples include summarizing public research or drafting language from non-sensitive material. A governed enterprise workspace, basic source review, and ordinary identity controls may be sufficient.
Material but reviewable
Examples include searching internal documents, preparing portfolio commentary, or comparing due-diligence records. Add approved-source restrictions, role-based retrieval, citations, output review, and stronger logging.
Consequential action
Examples include moving money, changing permissions, sending instructions, altering books and records, or producing advice relied on without review. Require explicit authorization, dual control where appropriate, narrow tools, transaction limits, independent monitoring, and tested reversal or containment.
Human oversight must name the human.
“Human in the loop” is too vague for a control. Name the role, the evidence that person sees, the decision they make, and what happens if they are unavailable.
Build governance around a real use case.
- Inventory current tools, including unsanctioned use and AI features embedded in existing software.
- Classify the information the first use case needs and the harms that could follow from disclosure or error.
- Assign an executive owner, technical owner, reviewer, and incident contact.
- Approve the model, data flows, retention, access, and vendor terms.
- Test ordinary tasks, misuse, prompt injection, unavailable sources, and incorrect outputs.
- Review access and performance on a schedule tied to risk, not a generic annual calendar.
The private-wealth AI threat model supplies the misuse cases. The build, buy, or steward framework helps assign long-term operating responsibility.
Questions family offices ask before deciding.
Who should own AI governance in a family office?
The family or its delegate should set risk appetite. A named executive owner should approve use cases, while technology, security, legal, and business owners hold defined implementation and review duties.
What belongs in a family office AI policy?
Allowed and prohibited uses, data classes, approved tools, access rules, review requirements, agent limits, logging, vendor diligence, incident handling, exceptions, and continuity.
Should prompts and outputs be retained?
Retention should match the use case, legal obligations, privacy requirements, and the need for audit evidence. A single default is unlikely to fit public research, sensitive family records, and consequential actions.
How often should AI controls be reviewed?
Review frequency should follow risk and change. Reassess when a model, vendor, integration, data source, permission, or use case changes, and schedule periodic access and incident reviews.
How should outside advisers receive access?
Use named accounts, narrow permissions, defined purpose, time limits, logging, and prompt removal. Shared accounts make accountability and revocation harder.
References used for this guide.
- NIST, AI Risk Management Framework
- PwC, “How AI is reshaping the modern family office,” June 8, 2026
- OWASP, Top 10 for Large Language Model Applications
Published 2026-07-12. Review product terms, legal duties, and security requirements against the family office’s current facts before implementation.
Continue the decision.
Define the boundary before choosing the tool.
A private briefing starts with the family’s information, risk, team, and first practical use case.
Request a private briefing