Prologue
According to Deloitte report there are currently 8,030 family offices worldwide, collectively managing approximately $3.1 trillion in assets. This total is projected to increase by 73 percent, reaching $5.4 trillion by 2030, which would exceed the present
global hedge fund industry’s assets under management ($5 trillion). The number of family offices is anticipated to rise to 10,720 by 2030. North America is the largest, wealthiest hub for family offices, Europe the oldest, and Asia Pacific the fastest growing.
Family offices have traditionally been slower to adopt emerging technologies; however, the expectations of younger family members are driving demand for AI-enabled solutions that provide real-time insights and hyper personalised content. Additionally, with
the growing allocation to alternative investments and the voluminous data associated with this asset class, family offices are witnessing increasing dependence on advanced technology and integration of AI powered tools.
Family offices that integrate AI into their operations will achieve enhanced efficiency and deliver superior client service, whereas those that do not may face competitive disadvantages.
Key priorities for technology adoption
According to Citibank’ 2025 Global Family Office Report, the top priorities for technology adoption includes investment management and data analytics platforms (50%), consolidated reporting (39%), and cybersecurity & data protection (37%). Additionally,
AI & machine learning (28%) was cited ahead of the remaining priorities including accounting and document management. Apart from these Family member education tools (18%), Alternative investment management (10%) are among the other stated priorities.
They key barriers to technology adoption in the family office includes lack of internal expertise (57%) as well as a lack of awareness of available options (34%). Furthermore, cybersecurity or privacy concerns (28%) and uncertainty over return on investment
(25%) are also obstacles for technology adoption.
Early adopters of AI are using its core capabilities to provide comprehensive portfolio insights, highly personalised market research on emerging themes and investment recommendations, as well as streamlined process automation.
Select industry leading examples
The following industry-leading examples illustrate approaches to serving high-net-worth individuals, and family offices will find these use cases valuable when developing their own AI strategies.
- HSBC Private Bank has launched “Wealth Intelligence” to client facing staff, investment counsellors, and product specialists to provide quality market insight and hyper personalised investment strategies to high-net-worth customers. The
tool will be further enhanced to support the screening and identification of appropriate investment products, enabling advisors to discuss investment options and asset allocation recommendations with clients. - Bank of Singapore launched agentic AI-powered tool that automates KYC due diligence. Source of Wealth Assistant (SOWA) helps relationship managers create more consistent and compliant Source of Wealth reports, reducing turnaround time from
10 days to one hour and improving account opening efficiency. Relationship managers review and edit AI-generated SoW reports before sending them to internal teams for anti-money laundering and counter-terrorism financing checks. - Citi Wealth has launched “AskWealth” a GenAI-powered conversational assistant that allows to resolve client inquiries with ease and speed, and advisors can access timely market insights and research to answer questions related to their
clients and portfolios. - Morgan Stanley Wealth Management will integrate a new AI-driven feature from
BlackRock’s Aladdin Wealth platform into its portfolio risk management system. The “Auto Commentary” tool translates complex portfolio analytics and individual client investment preferences into actionable insights, enabling financial advisors
to provide tailored narratives and foster deeper client engagement through more meaningful and differentiated conversations. - Royal Bank of Canada’ U.S. wealth management arm has partnered with TIFIN AG to equip the financial advisors with AI-Powered Insights, to observe client behaviours and patterns to identify those who might have money in motion following
a significant financial event. It allows to deepen the client relationships and spot potential missed opportunities. - Blackrock developed an AI powered virtual investment analyst (Asimov) for firm’s equity research. It analyses research notes, scans company earnings reports and generate hyper personalised portfolio insights. It demonstrates the way AI
is evolving beyond simple automation to become a collaborative tool for investment professionals.
Implementing AI in Family Offices: A Structured Approach
AI has potential to transform the family offices by streamlining processes and automating routine tasks, AI will allow family office advisors to dedicate greater attention to strategic and value-added activities. Key considerations for AI powered solutions
include,
- Task Selection for Automation: Implementing artificial intelligence within a family office involves much more than simply integrating AI powered tools into existing systems. The process must begin with a clear identification of
tasks that are most amenable to automation. Priority should be given to processes that are straightforward to validate, ensuring that the automation delivers reliable outcomes. For example, client onboarding, new account opening, investment research. - Choosing Appropriate AI Models: It is essential to select the right AI models for specific tasks, as each model is designed to address distinct functions. Relying on a single, universal model is ineffective; instead, family offices
should match AI models with the requirements of each task. This tailored approach enhances both accuracy and relevance of AI-generated outputs. - Training for Effective Interaction: Once AI-generated insights are made available to advisors, it is important that users are equipped to interact with these tools effectively. Proper training is necessary to enable users to create
targeted prompts, thus ensuring that they extract information that is both pertinent and precise. - Preparing Data and Workflows for AI: Family offices need to ensure their data and workflows are suitably prepared for AI integration. While large language models (LLMs) excel at interpreting documents, they often face challenges
when working with structured databases. For addressing this challenge, family offices are advised to implement knowledge graphs and vector databases, as these tools furnish essential contextual information for AI systems. - AI governance: Family offices must implement an AI governance framework to ensure transparency, accountability, and fairness. This includes clear standards for data use, model explainability, and decision-making. Effective governance
supports responsible AI innovation while reducing risks like bias, privacy breaches, and security threats. Additionally, the firm should consider implementing automated tools to enable comprehensive AI governance and expedite responsible AI adoption (for example,
watsonx.governance or OneTrust).
Conclusion
AI is significantly advancing family office technology; nevertheless, achieving optimal results depends on strategic implementation that integrates AI’s capabilities with human oversight and expert domain knowledge. AI led transformation will benefit for
both single-family offices (SFOs) and multi-family offices (MFOs) including intelligent data management, automated reporting, enhanced governance, and the ability to identify new investment opportunities, leading to increased efficiency and potential returns.
The AI powered solutions will allow family offices to unlock efficiencies, deepen insights, and deliver better outcomes for UHNW clients.
