In the ever-evolving landscape of wealth management, the integration of Artificial Intelligence (AI) is no longer a futuristic concept but a present-day reality. This is particularly evident in Singapore, where the independent wealth management sector is witnessing a paradigm shift. The Hubbis Independent Wealth Management Forum - Singapore 2026 brought together industry leaders to explore the intricate relationship between AI and the future of independent wealth management. The discussion was a testament to the fact that while AI is a powerful tool, its true value lies in how it is harnessed and integrated into the core operations of wealth management firms.
The People-Centric Nature of Independent Wealth Management
One of the key takeaways from the forum was the emphasis on the people-centric nature of independent wealth management. Despite the allure of AI, the panel consistently stressed that the relationship between the advisor and the client remains at the heart of the business. Hrishikesh Unni, Managing Director at Taurus Wealth Advisors, succinctly put it: "AI should not be adopted because it is fashionable - it should be adopted because it helps the firm deliver more of what the client actually came for."
This sentiment underscores the importance of personalized advice and close alignment with clients, which are hallmarks of independent wealth management firms. Therefore, technology adoption must be strategic and aligned with the firm's client promise.
The Early Stages of AI Adoption
While the potential of AI is undeniable, the sector is still in its early stages of adoption. Smaller EAMs and MFOs are often testing off-the-shelf tools, assessing their effectiveness, and staying attuned to regulatory expectations. However, the market is moving quickly, and the focus is shifting from experimentation to execution. Jackson Ng, Chief Operating Officer at Azimut Group, noted that the next phase will be defined by institutional AI, where shared context, governance, and integration into business processes become crucial.
From AI Capability to Business Application
A recurring theme was the need to bridge the gap between AI capability and business application. AI tools, while powerful in isolation, often fail to translate into tangible business outcomes if not properly embedded into the daily work of advisers, investment teams, operations, compliance, and management. The key is to identify specific workflow problems and set clear success metrics before selecting technology. This approach ensures that AI is not just a tool but a strategic asset that solves real business problems.
Relationship Managers: The Scarce Resource
The panel also highlighted the critical role of relationship managers (RMs) in independent wealth management. Senior adviser time is a valuable yet scarce resource, and RMs often spend a significant portion of their week on non-revenue-generating activities. AI can help by reducing administrative work, improving preparation, and streamlining meeting follow-up, allowing RMs to focus on activities that drive trust, revenue, and retention. This is particularly relevant in a market where UHNW and HNW clients often maintain relationships across multiple banks and advisers.
AI Beyond Cost Reduction
While AI is often discussed in terms of cost reduction, the panel emphasized its revenue potential. AI can support prospecting, client segmentation, engagement planning, service consistency, and share-of-wallet growth. By engaging clients more intelligently and consistently, independent firms can be better positioned to capture consolidation opportunities and protect relationships from competitors. This shifts the investment case for AI, making it a revenue-enabling layer across the client base.
Build, Buy, or Partner: A Realistic Assessment
The build, buy, or partner decision is a critical one for independent wealth managers. Building proprietary AI infrastructure from scratch is often impractical due to the high costs and maintenance burden. Panellists warned that firms often underestimate the complexity and speed of iteration required to keep pace with rapidly evolving technology. Even examples that appear to be internal builds may involve significant external partnerships. Therefore, buying or partnering may be the more realistic path for smaller firms, with the comparison being the cost of hiring additional people to perform manual work.
Technology Budgets: Reflecting Strategic Importance
When it comes to allocating technology budgets, panellists suggested that firms should think seriously about increasing their spend. The comparison should not only be against the current technology budget but also against the cost of hiring additional staff. The argument is not about aggressive spending without discipline but about assessing AI in terms of its strategic value. If AI saves meaningful adviser time, improves client engagement, or increases revenue opportunities, the budget should reflect that.
Outcomes Matter More Than Speed
The panel cautioned against implementing AI simply for the sake of being first. Wealth management clients evaluate an adviser based on outcomes, trust, responsiveness, and the value they receive. Therefore, firms need to balance speed with discipline. AI is moving quickly, and opportunity cost matters. However, rushed adoption without clear use cases, controls, or integration can create operational and reputational risk.
Cybersecurity and Data Protection: Core to AI Adoption
As firms build AI ecosystems, cybersecurity and data protection become paramount. Client data is confidential, and trust is central to the advisory relationship. Firms must consider data confidentiality, cybersecurity, regulatory compliance, and governance in their AI strategy. This is particularly sensitive in wealth management, where cross-border considerations can be complex. Security needs to be part of the AI budget and implementation plan, not an afterthought.
Clients Are Using AI Too
The panel noted that clients themselves increasingly have access to the same broad AI tools as advisers. This changes the client conversation, with some remaining sceptical and others using AI heavily to inform their investment decisions. Advisers need to be prepared to explain, contextualize, challenge, and refine AI-generated information. This reinforces the importance of adviser judgment in interpreting AI-supported processes in the context of client objectives and risk tolerance.
Cultural Adoption: Beyond Age
Finally, the discussion turned to cultural adoption. Panellists challenged the assumption that AI adoption is purely an age-related issue. While younger employees may be more comfortable with new tools, openness to AI ultimately depends on leadership, firm culture, and perceived usefulness. The challenge is not just giving staff access to tools but creating a framework where those tools are used consistently and effectively across the firm. This points back to the need for enterprise AI, where shared practices, training, governance, and institutional context are crucial.
The Future of Independent Wealth Management in Singapore
In conclusion, AI will play an increasingly important role in the future of independent wealth management in Singapore. The opportunity is not just to automate tasks but to reshape how firms support advisers, engage clients, manage workflows, and scale relationship-led advice. However, the benefits will not come automatically. Firms need to define their proposition, select focused use cases, manage security and compliance, invest appropriately, and build a culture of adoption. The most successful firms will be those that use AI to strengthen, rather than dilute, the relationship model, ensuring that the client outcome remains the ultimate test.
