When families ask AI for a family office, who gets named?
We put 100 real buyer questions to ChatGPT and Gemini and Perplexity and checked which of 20 global multi-family offices and bank-run family office practices each answer named. 45 of the 100 questions got no named firm at all — a global read spanning the US, UK/Europe and Switzerland, since family offices and their clients are inherently cross-border. Run the check for your firm →
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Why we ran this
Family offices are the most relationship-driven, referral-dependent corner of wealth management — and referrals increasingly start with a question to an AI assistant, not a phone call. The assistant assembles its answer from a handful of sources — firm sites, industry press, forums, LinkedIn — and either names specific firms or it doesn’t. This benchmark reads how visible family offices and multi-family offices currently are, engine by engine, and where the openings are, globally rather than in one market alone.
How we measured it
We wrote 100 questions in the language a prospective family, adviser or journalist actually uses, across six topic clusters (all 100 are explorable in full below). Each question was sampled once per engine, and every answer was checked for a mention of any of 20 identifiable global family offices — from independent multi-family offices like Pathstone and Stonehage Fleming to bank-run family office practices at UBS and J.P. Morgan — using the same name matcher a live Inserviss scan uses.
A single pass per engine establishes direction and priority; it is not a trend line. Citations are reported as measured; query volumes are labelled estimates, shown as ranges. Engines are never blended. This run covers ChatGPT and Gemini and Perplexity; Microsoft Copilot is not currently sampled.
What we found, at a glance
- Visibility varies sharply by engine. ChatGPT named a tracked firm in 13 of 100 answers, Gemini named a tracked firm in 55 of 100 answers and Perplexity named a tracked firm in 16 of 100 answers.
- 45 of 100 questions got no tracked firm on any engine. Weakest: Fees, Structure & Governance, Investment Approach & Direct Investing, Succession, Next-Gen & Philanthropy.
- UBS is the most-named firm, appearing in 38 of 300 answers. Only 13 of the 20 tracked firms were named even once.
- Independent multi-family offices and bank-run practices get named at very different rates. See the full breakdown, and which archetype AI actually favors, in the table below.
How often does AI name a firm at all?
Below is the share of the 100 answers that named at least one tracked firm, per engine — then the full table, every firm against every engine, sortable by any column.
Share of 100 answers naming at least one of the 20 tracked firms. Per engine, never blended.
| Firm | ChatGPT | Gemini | Perplexity |
|---|---|---|---|
| UBSbank | 4 | 24 | 10 |
| Stonehage Fleming | 3 | 32 | 0 |
| Rockefeller Capital Management | 0 | 23 | 1 |
| Bessemer Trust | 3 | 20 | 0 |
| Northern Trustbank | 3 | 19 | 0 |
| Cresset | 6 | 10 | 4 |
| J.P. Morgan Private Bankbank | 3 | 9 | 4 |
| Goldman Sachsbank | 0 | 6 | 4 |
| Pathstone | 0 | 7 | 0 |
| Ballentine Partners | 0 | 6 | 0 |
| Kaiser Partner | 0 | 2 | 1 |
| Citi Private Bankbank | 1 | 2 | 0 |
| BNY Wealthbank | 0 | 1 | 0 |
| Athena Capital Advisors | 0 | 0 | 0 |
| Summit Trail Advisors | 0 | 0 | 0 |
| Tolleson Wealth Management | 0 | 0 | 0 |
| Waldron Private Wealth | 0 | 0 | 0 |
| Sandaire | 0 | 0 | 0 |
| Cazenove Capital | 0 | 0 | 0 |
| J. Stern & Co | 0 | 0 | 0 |
Mentions across 100 answers per engine. Select a column heading to re-sort. Scroll the table sideways on a narrow screen.
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Where the openings are
Coverage varies by question type. Below is the best engine’s coverage for each cluster, out of ~17 questions.
Answers naming a firm on the strongest engine, per cluster (out of ~17).
How this is estimated
Estimate — a range, not a keyword-tool export. Illustrative estimate, not a keyword-tool export. Each cluster has ~16-17 seed buyer questions; long-tail intent phrases run ~25–130 monthly searches each across the combined US / UK-Europe / Switzerland population, one or two head terms add ~300–1,000/mo, and an AI-assistant reformulation multiplier of ×2–4 accounts for the wider phrasing people use with an assistant. Ranges are rounded and widened. For a specific firm, the real number comes from the check, not this table.
| Cluster | Best-engine coverage | Est. questions / mo |
|---|---|---|
| Choosing a Family Office or MFO | 13/17 | 2,800–10,500 |
| ●Fees, Structure & Governance | 5/17 | 1,800–7,000 |
| ●Investment Approach & Direct Investing | 11/17 | 2,000–7,800 |
| ●Succession, Next-Gen & Philanthropy | 8/17 | 1,900–7,300 |
| ●Tax, Trusts & Cross-Border Structuring | 11/16 | 1,700–6,600 |
| ●Reporting, Operations & Custody | 7/16 | 1,300–5,200 |
Volumes are an estimate, shown as a range. Illustrative estimate, not a keyword-tool export. Each cluster has ~16-17 seed buyer questions; long-tail intent phrases run ~25–130 monthly searches each across the combined US / UK-Europe / Switzerland population, one or two head terms add ~300–1,000/mo, and an AI-assistant reformulation multiplier of ×2–4 accounts for the wider phrasing people use with an assistant. Ranges are rounded and widened. For a specific firm, the real number comes from the check, not this table.
The check runs this same 100-question universe against your firm’s name, per engine, and returns your AI Visibility Score plus the exact questions where a competitor — or no one — is being named.
Check your firm’s AI visibility →Explore the 100 questions
Every question, and exactly what each engine did with it — which firms it named, and which sources it pulled from. Filter by cluster, search for your own name, or show only the questions no firm has claimed.
The 45 questions no tracked firm owns on any engine, with the sources AI cites instead — a ready-made content brief.
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Where each engine gets its answers
The domains each engine actually pulled from, per engine — never blended. ChatGPT leans on Forbes, professional-services sites (PwC) and Campden Wealth, the dedicated family-office trade press. Perplexity repeats LinkedIn and Reddit alongside family-office software and advisory platforms (Aleta, AndSimple, AssetVantage). Gemini names tracked firms most often of the three, but pulls from a long, thin tail of smaller wealth and family-office blogs rather than a handful of dominant sources.
Times a domain was cited across the 100 answers. Blue = a tracked firm’s own site.
About this study
- Single pass per engine. One sample per question per engine establishes direction; it does not average out run-to-run answer variance.
- Snapshot in time. Collected September 5, 2026. AI engines change their answers week to week; this is not a trend line.
- Conservative name matching. Short one-token names (UBS, Cresset, Sandaire…) require an exact whole-word match, so a slight undercount is possible — but it cannot explain a 45-of-100 gap.
- ChatGPT and Gemini and Perplexity this run. Microsoft Copilot is not currently sampled; the measurement is identical when it is.
How to cite this study
To request the underlying data or discuss a firm-specific analysis, contact igor@inserviss.app.
The same measurement, run against your name — per engine, question by question — with your score and the questions to claim first.
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