Key Takeaways
- • Squire Patton Boggs warns that AI is rapidly embedding itself in family office technology and operations, but that its use without governance and guardrails could become a significant area of strategic risk.
- • The firm identifies nine risk areas for family offices, including model-level risks, hallucinations and automation bias, data exposure, cybersecurity, AI-enabled fraud and social engineering, vendor opacity, regulatory exposure, and organizational and reputational harm.
- • Family offices are described as high-value targets because of concentrated wealth, sensitive personal data, lean teams, and reliance on informal communication, making them susceptible to AI-generated impersonation such as voice cloning and deepfakes.
- • The recommended governance response includes use-case inventories with risk classification, understanding deployed systems, AI policies aligned with data governance, human oversight and accountability, supply chain mapping, and AI literacy training.
Summary
Squire Patton Boggs has published the first instalment of a two-part series on managing AI and cyber risks in the family office sector. According to the firm, AI is increasingly embedded in family office technology infrastructure, with principals seeking efficiency gains, better decision quality and more effective systems across lean teams. The firm argues that AI can streamline processes and synthesize complex information, but that the central challenge is no longer whether AI can deliver productivity gains, but how those gains can be realized within a controlled, risk-aligned framework.
The article outlines several categories of AI-related risk specific to family offices. Model-level risks may be difficult to detect in routine operations, with biases from historical training data producing systematically skewed outputs and models experiencing drift as data patterns and regulations evolve. The firm highlights hallucinations that are "convincingly wrong" and the associated risk of automation bias, which can cause AI to shift from a decision-support tool into an implicit decision driver in investment contexts. Data exposure is flagged as a particular concern, since sensitive information about multigenerational families may be processed outside the organization's control through ordinary use, without a discrete breach event.
On security, the firm notes that family offices manage significant wealth concentration, sensitive data and complex multi-entity transactions, making them high-value targets. It warns that AI is being used to enhance fraud and social engineering, including convincing written communications and voice cloning or deepfakes to impersonate trusted individuals. Vendor opacity, where third-party AI providers' underlying models and data practices are not fully transparent, and regulatory exposure under existing frameworks such as data privacy regimes, are also highlighted. The article cites UK guidance from the Information Commissioner's Office and the Financial Conduct Authority, as well as the EU AI Act, as examples of evolving oversight.
For governance, the firm recommends a proportionate, coordinated approach: maintaining an inventory of AI use cases categorized by risk, understanding the types of models deployed, establishing internal AI policies aligned with data governance, ensuring human oversight with clear accountability, mapping AI supply chain dependencies and reviewing contractual terms on data use, and training staff to recognize hallucinations, bias and AI-enabled threats.
The article outlines several categories of AI-related risk specific to family offices. Model-level risks may be difficult to detect in routine operations, with biases from historical training data producing systematically skewed outputs and models experiencing drift as data patterns and regulations evolve. The firm highlights hallucinations that are "convincingly wrong" and the associated risk of automation bias, which can cause AI to shift from a decision-support tool into an implicit decision driver in investment contexts. Data exposure is flagged as a particular concern, since sensitive information about multigenerational families may be processed outside the organization's control through ordinary use, without a discrete breach event.
On security, the firm notes that family offices manage significant wealth concentration, sensitive data and complex multi-entity transactions, making them high-value targets. It warns that AI is being used to enhance fraud and social engineering, including convincing written communications and voice cloning or deepfakes to impersonate trusted individuals. Vendor opacity, where third-party AI providers' underlying models and data practices are not fully transparent, and regulatory exposure under existing frameworks such as data privacy regimes, are also highlighted. The article cites UK guidance from the Information Commissioner's Office and the Financial Conduct Authority, as well as the EU AI Act, as examples of evolving oversight.
For governance, the firm recommends a proportionate, coordinated approach: maintaining an inventory of AI use cases categorized by risk, understanding the types of models deployed, establishing internal AI policies aligned with data governance, ensuring human oversight with clear accountability, mapping AI supply chain dependencies and reviewing contractual terms on data use, and training staff to recognize hallucinations, bias and AI-enabled threats.
Go deeper than the headline
Research every firm in this story, track the ones that matter and get the daily briefing — free for 7 days.