How should family offices govern AI adoption?

Family offices should govern AI adoption by answering four questions before any deployment: What data does the tool see, and does the vendor retain or train on it? What decisions is it influencing, and what is the stakes level (low, medium, or high)? Who is the named human accountable for its outputs? And how is it being evaluated over time as the vendor updates the model? Control intensity should match decision stakes — a single enterprise policy that treats scheduling tools and investment analysis tools identically fails at both ends. As with other technology decisions, AI counsel should come from advisors independent of the AI platform vendors.

AI adoption in family offices is accelerating. Principals are asking about it. Boards are asking about it. Operating companies are deploying it, often ahead of any governance structure to evaluate what they have deployed.

The risks are real but manageable. What family offices need is not an AI policy copied from a Fortune 500 playbook, and not a panicked moratorium. What they need is a governance framework calibrated to how family offices actually operate. Here is the one we use.

The four questions every AI deployment should answer

Before any AI tool is deployed in a family office environment, four questions should be answered in writing. Not at the enterprise-policy level — at the individual-deployment level.

1. What data does it see?

Every AI tool processes input data. Some of it stays inside the family office's environment; much of it does not. For each AI deployment, document: what inputs does this tool receive, does the vendor retain those inputs, does the vendor use those inputs to train models, can the inputs be accessed by vendor employees, and under what jurisdictions is the data processed.

A family office assistant that summarizes emails into an AI chatbot is, by default, sending family financial information to a vendor. That may be acceptable with the right vendor and the right contractual protections. It is not automatically acceptable.

2. What decisions is it influencing?

AI tools rarely make decisions directly. They shape the inputs to decisions — by summarizing documents, by suggesting responses, by drafting analyses, by surfacing signals from data. Every AI deployment should be categorized by the kind of decisions it influences:

The family office's AI governance should match control intensity to decision stakes. A single enterprise-wide AI policy that treats scheduling tools and investment analysis tools identically is wrong at both ends.

3. Who is accountable for its outputs?

AI does not absorb accountability; people do. For every AI tool in the family office, there should be a named human who is accountable for the quality of its outputs. If the AI tool drafts a response to a vendor, someone is accountable for sending it. If it summarizes a legal document, someone is accountable for the summary being accurate. If it produces a risk assessment, someone is accountable for the assessment's validity.

The accountable person must have the standing and the time to review outputs before they leave the family office — or to publicly acknowledge that review has been delegated to the tool and the risk accepted. What cannot be allowed is the middle ground: outputs going out with no human accountability and no acknowledgment that the AI is running unsupervised.

4. How is it being evaluated over time?

AI tools change. Vendors update models without notice. Capabilities that worked reliably last month may degrade this month; vendors may deprecate features, add features, change pricing, or change the way they handle data. AI deployments in the family office should be reviewed on a documented cadence — quarterly at a minimum for medium-stakes tools, monthly for high-stakes tools.

The vendor-independence principle applies here too

The AI vendor market is currently dominated by a small number of large platforms — OpenAI, Anthropic, Google, Microsoft. Most technology consultancies have reseller or partner relationships with one or more of them. That shapes their AI recommendations.

Family offices should evaluate AI deployments the way they evaluate any other technology deployment: with counsel that has no partnership with the AI vendors involved. That usually means specific AI tools will be recommended for specific use cases — the right tool for the right job, not the right tool for the advisor's partnership portfolio.

The bottom line

AI is neither magic nor menace for family offices. It is another category of technology deployment that requires governance proportional to its impact. The four-question framework above — data exposure, decision influence, human accountability, ongoing evaluation — is a defensible structure that scales with the family office's AI usage without adding bureaucratic overhead to deployments that do not need it.

The families that deploy AI thoughtfully now will not need to retrofit governance onto it later. Both are possible; the first is substantially cheaper.

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