As family offices explore how artificial intelligence can enhance productivity, they are also weighing the risks that come with AI use, from data security and governance to staffing.
One of the key challenges for family offices in 2026 will be determining “how to incorporate AI into their tech stack while managing cybersecurity and data integrity,” says Joshua S. Miller, CEO of Minot’s Light Management.
Across family offices, AI is being “adopted primarily as a practical productivity and decision-support tool,” says Christopher Dickson, national family office advisory leader for RSM US LLP, supporting activities such as meeting documentation and early-stage drafting and brainstorming — with some business reporting and analytics functionality.
While these use cases can improve efficiency and help teams focus on higher-value work, they also introduce new governance, data privacy, legal and reliability considerations.
As a result, Dickson says, “family offices should treat AI as an extension of their existing technology and risk management framework — clearly defining acceptable use, data handling expectations, oversight and auditability requirements, and the role of human review, and implementing higher-risk use cases in coordination with legal and compliance advisors.”
As they seek to capitalize on AI’s capabilities, family offices need to manage AI-related operational risks in a number of areas:
* Data privacy and security. As AI tools are increasingly used across the family office, “there can be varying levels of awareness about the privacy implications — particularly how data is handled, what happens to information that is entered, and whether or how it may be used by the model,” Dickson says.
Confidentiality risks may be amplified in the family office context.
“The only way you really get AI to work for you is if you’re willing to contribute some of your data so that it understands what you’re trying to do,” says Stacy Dick, operating partner at Wingspan Legacy Partners. “And that means exposing what is typically highly confidential information to an AI program and sponsor who may or may not know how to control the usage of that information.”
Enterprise AI tools may offer more robust data protection options.
“If you’re using public models, you need to be careful. Nothing in this world is free,” Dickson says. “Private and confidential data could inadvertently be used to train a model or could potentially be exposed.”
* AI integration across the technology stack. Family offices need to think beyond standalone solutions to individual technology problems.
“Historically, many family offices have approached technology through point solutions — for example, implementing a better general ledger system or a new document management system,” Dickson says. “With AI, however, it can no longer be treated as a standalone technology project. It needs to be considered an enterprise-wide initiative.”
* Data governance. AI tools are only as good as the underlying reporting architecture, and fragmented systems and incomplete data present risks. Family offices need to make sure their data governance policies are up to date.
“If you have the same data in multiple systems, are those data sets reconciled? If not, which source will the AI rely on — and what happens if one of them is incorrect?” Dickson says. “If the data is not connected to your estate plan, for example, could the system generate recommendations that are incomplete or misleading because it is not considering the broader planning context?”
Permissions and privacy are also an essential part of data governance.
“Could an AI tool pull data from one system and surface it in another — such as displaying the CEO’s compensation in a context where it should not be visible?” Dickson says. “Restrictions, permissions and access controls become especially important as family offices begin to use more advanced, agent-based AI that can operate across multiple systems. Strong data governance is essential before enabling those capabilities.”
Family offices should also consider whether, and to what extent, they can retain and review records of AI prompts, data inputs and generated outputs, in order to support oversight, accountability and internal governance expectations, Dickson says. In all these areas, consultation with legal counsel is encouraged, Dickson notes.
* Staffing. Some family office professionals may have understandable questions about how increased use of AI could affect roles and responsibilities within already lean teams.
In practice, though, family offices do not appear to be using AI to reduce the size of their staffs, at least not yet, Dickson says.
“Family offices are typically lean, and AI use cases to date have been fairly narrow. The focus is less on replacing staff and more on augmenting existing teams — so they can spend less time on manual data entry and reconciliation, and more time on the value-added work they provide in supporting the family,” Dickson says.
The fact that family offices tend to be lean can also increase the potential value of AI tools.
“I think there is real value in reducing some of the underlying manual processes,” Dickson says. “Teams already face capacity constraints because of that work, and this can help free them up to focus on where they should be spending their time.”
* Guardrails and training. Family offices need a clear approach for validating and pressure-testing any insights or recommendations produced by AI, including defining when independent review, human judgment or alternative analysis is required before decisions are made.
An AI use policy should clearly define when and how AI tools may be used, what risks the family office is willing to accept, and what types of data may — or may not — be entered into AI systems, Dickson says. Training for both family members and professional staff is also critical.
“There needs to be training on appropriate use cases, associated risks, and the level of documentation and validation that is expected — so that people understand they cannot rely on AI outputs on their own, particularly given the risks of hallucinations and bias,” Dickson says.