A few days after providing a client with a detailed Statement of Advice, I noticed something unusual. The client returned with a series of questions that were unlike any I had seen before. At first glance, they seemed routine, but the depth and focus of the queries made me pause.
The client had used AI to interrogate the SOA, exploring corners of the advice that even our walkthrough had barely touched. Some questions were brilliant, proposing alternative scenarios or cross-checking assumptions. Others felt robotic, lacking emotional nuance or real-world context. A few were slightly off the mark, generated without a human filter. It was a reminder that technology can amplify curiosity, but it does not replace experience or judgment.
One question stood out. The client asked about holding two additional properties inside their SMSF using a Limited Recourse Borrowing Arrangement. The AI-calculated projections suggested that total assets could be higher than our recommended scenario. On paper, it looked appealing. But reality told a different story. Adding two properties would likely result in negative cash flow for the first five years, introduce stress due to high leverage, reduce diversification since the client already owns seven properties, and add significant administrative complexity. The numbers made sense, but they ignored human tolerance and practical limitations.
Another query involved shifting the timing of an investment bond contribution. Technically, it could improve returns. Yet the AI did not consider the practicalities such as bank processing times, paperwork, or the client’s capacity to manage multiple deadlines. It was the gap between theoretical optimisation and real-world decision-making.
There were also questions about investing in a particular international equity fund that did not align with the client’s risk profile or values. While the suggestion was technically correct, it lacked an understanding of emotional factors, such as how much volatility a client is comfortable with or whether the investment aligns with their social and ethical priorities. Human judgment was essential to guide the client through the reasoning and explain why it was not suitable.
These interactions offered a glimpse of the future of financial advice. Clients are beginning to engage more actively, armed with AI tools that generate unexpected, unconventional, and sometimes misleading questions. Advisers must increasingly act as interpreters, separating feasible strategies from theoretical anomalies and guiding clients through both numbers and the emotional realities of their decisions.
This is not about AI replacing human advisers. It is about enhancing engagement, transforming conversations, and uncovering opportunities that might otherwise go unnoticed. AI can highlight gaps, accelerate understanding, and suggest new possibilities. But it cannot replicate experience, empathy, or the strategic insight needed to protect long-term wealth.
For advisers, this presents both challenges and opportunities. Our role is evolving from information provider to strategist, educator, and protector of clients’ broader financial health. Balancing AI-generated insights with human judgment will define the next generation of advice. Clients may arrive with technically correct but practically flawed questions. Our job is to turn these into meaningful discussions, ensuring decisions are sustainable, aligned with goals, and grounded.
Technology is changing the pace and style of engagement, but it also elevates trust, empathy, and professional judgment. Advisers who embrace this shift will guide clients through a landscape where AI-informed curiosity meets human insight, producing richer dialogue, deeper engagement, and more thoughtful decisions.
To handle AI-generated client questions ask the client to send the AI prompt and the answer. Then test the idea against cash flow, diversification and administration complexity, and offer a human explanation for why the strategy isn’t appropriate.
Sangram Rana is a Melbourne-based financial adviser, accountant, and registered tax agent, specialising in SMSFs, risk protection, and intergenerational wealth strategies.
