The permission to begin
Most family offices aren't resisting AI. They're waiting for clarity that isn't coming. Here's how to start without exposing what you can't afford to.
Most family offices are not opposed to AI. They are frozen. The tools are visible. The potential is understood. The ads and demos have been impressive. But when it comes to actually using AI with real data in a real workflow, the questions stack up faster than the answers. Can we send client data to this platform? What does our regulator actually say about this? What are the retention terms? What happens if something leaks?
When you can’t see where you’re driving, the rational response is to stop.
And so, most offices do.
The difficulty is that the clarity they are waiting for is not arriving any time soon. The EU AI Act mandates that member states establish regulatory sandboxes for AI, but most are still being designed. Over 60 AI-related sandboxes exist globally, yet almost all are government-run and sector-specific, built for fintech or healthcare, not for family offices managing private wealth across multiple jurisdictions. There is no industry framework that tells a five-person office exactly what it can and cannot do. And there may not be one for years.
Waiting for that framework means standing still while the gap between available capability and actual adoption continues to widen.
Starting without exposure
The path forward does not require the office to send sensitive family data to a cloud platform on day one. It requires a structured approach to experimentation that respects the constraints of a high-trust environment.
Interested in learning more about what’s actually possible with AI and the options for family offices?
The first step is to separate the learning from the risk. Create anonymised or synthetic versions of real datasets: portfolio structures with changed names and numbers, sample legal documents with fictional entities, representative communication patterns rather than actual ones. Run AI tools against this layer first. The office learns what the technology can do, how it handles complexity, and where it falls short, all without any genuine exposure.
The second step is to pick a single, low-sensitivity workflow and test it with clear boundaries. Meeting note summarisation. Research digests. Draft communications that will be reviewed before sending. Choose something repetitive, time-consuming, and low-risk. Run it for 30 days. Evaluate what the tool produces, what it misses, and what the team learns about working alongside it. RSM has observed that the shift for family offices should be from apprehension to readiness, and a bounded pilot is how that shift begins.
Know what you’re connecting to
Before any cloud-based tool enters the workflow, apply the same due diligence the office would use for any other relationship of this sensitivity. Where is the data stored? Under which jurisdiction? What are the retention policies? Does the provider train its models on your inputs? What happens to your data when the contract ends? Several enterprise AI tools now offer zero-retention options, and understanding the difference between those and the default consumer products is part of the evaluation.
For offices that want to eliminate external exposure entirely, the option is increasingly practical. Open-source models running on local hardware, particularly Apple silicon, now offer meaningful capability without any data leaving the building. This will ofcourse require some infrastructure and maintenance and is not yet equivalent to the leading cloud-hosted models for every task, but for some work a family office does daily, the gap is closing fast.
One page before one tool
Before any of this begins, write a one-page AI use policy. Not a regulatory filing. Not a 40-page governance document. A single page that answers the questions the team is already asking: what data categories are off-limits for external AI tools? Which tools are approved, and for which tasks? Who reviews AI-generated outputs before they are used? What gets escalated?
This document does not need to be complex. It needs to exist. Its purpose is to replace silence with clarity, so the team has permission to act rather than permission to wait.
The offices that are moving
The family offices making progress with AI are not the ones that waited for perfect regulatory clarity. They are the ones that found a way to begin within the constraints they already understood. They started with synthetic data, picked a bounded workflow, audited their tools, and gave the team a clear framework for what was and was not acceptable.
This is not unfamiliar territory. The family office already knows how to manage risk, evaluate counterparties, and operate within uncertainty. AI experimentation is just another application of that same skill. The permission to begin does not come from a regulator. It comes from the office deciding that standing still carries its own risk.