AI is set to continue reshaping the infrastructure around financial advice and is likely to become more embedded within core systems over time, reducing reliance on separate tools and making its use more seamless, but as this plays out, questions around accuracy, data security, and governance need to be properly addressed, according to Hoxton Wealth.
Internal knowledge systems may allow advisers to access information more quickly, while workflow automation and agent-based processes can reduce delays and support consistency, helping make service models more cost-effective and broadening access to advice. However, these opportunities also introduce important considerations, the international financial advisory firm said in its white paper, 'AI and the Evolution of Financial Advice'.
“When something becomes easier, there is a natural tendency to lean on it,” said Chris Ball, CEO of Hoxton Wealth. “But in a profession built on professional judgement, this carries risk if it goes unchecked.”
The white paper highlights that AI outputs require careful review, particularly where accuracy is critical, warning that maintaining professional judgement will be key, as will avoiding over-reliance on automated outputs.
Client data must be handled securely and firms need clear governance frameworks to support responsible use, the paper said, and these frameworks will need to evolve. This will include defining the tools that are approved for use, setting clear guidelines on data handling and security, establishing review processes for AI-generated outputs, and ensuring that responsibility for decisions remains clearly assigned.
“In practice this is an extension of existing compliance and risk management processes," Ball said. "The objective is to ensure that new technology operates within the same standards that apply to all other aspects of the business.”
The white paper argues that firms may benefit from taking a measured approach to evaluating AI adoption and that rather than focusing on broad claims about transformation, it would be more useful to track specific outcomes, such as time saved on administrative tasks, improvements in document turnaround, reductions in compliance rework, and increases in adviser capacity.
These measures, the paper said, provide a clearer view of how AI is affecting the business in practice and how, over time, incremental improvements in multiple areas can combine to create a more efficient and scalable operating model.
It’s also important to preserve the human elements of advice, Ball added.
“While AI can improve efficiency, the value of financial advice continues to depend on human relationships and professional judgement. Clients look for clarity, reassurance, and a structured understanding of their financial position. These outcomes rely on communication, trust, and continuity.
"As firms introduce AI into their processes, it is important to ensure these qualities are maintained. Technology should support the delivery of advice, not distance the client from the adviser.”
