A new study released on September 8 by management consulting firm McKinsey & Company reveals that Hong Kong's financial advisory gap is expanding. While roughly half of all customers now utilize artificial intelligence before making purchasing decisions, half of financial advisors use AI less than once a week or not at all, indicating advisors are failing to keep pace with the rapid AI-driven reshaping of the industry.

The survey indicates that approximately 80% of customers purchasing major life, health, and wealth management products still rely primarily on financial advisors. However, the reason behind this reliance is practical rather than emotional: 43% want someone who understands their personal or family situation, 41% seek assistance in making significant decisions to avoid costly errors, 35% require immediate answers to complex questions, and 34% want accountability after completing a purchase.

In terms of AI usage scenarios, customers increasingly treat AI as a "second opinion," most commonly using it to identify potential financial and protection needs (35%), understand and compare relevant products (34%), and make purchase decisions (30%). When asked why they use AI, 58% cite more objective and consistent comparisons, 53% mention richer knowledge, 39% point to lower sales orientation, and 37% note a stronger connection between personal circumstances and insurance needs.

However, AI adoption on the advisor side lags significantly. Half of advisors use AI less than once a week or never, even though most remain open to AI playing a larger role in their work. Among work scenarios where AI is currently unused, "lack of suitable AI tools" was cited more frequently than "discomfort with AI use" — with one exception being prospecting and client development, where advisors show stronger protective instincts over front-line client relationships. This finding reshapes how the industry approaches AI adoption challenges: the core issue is not advisor resistance but rather the absence of appropriate tools. If financial institutions can provide more practical tools, realistic use cases, and clearer proof of effectiveness, AI adoption will accelerate.

McKinsey Senior Partner and Hong Kong Managing Director David Shih said that AI has not eliminated the need for insurance advisory consultations, but rather elevated the standard that quality advice must meet. Customers often arrive at meetings already armed with AI-generated information, comparisons, and questions, yet still seek advisors' judgment and accountability for major decisions. He believes the true dividing line will emerge between advisors who leverage AI to improve their performance and those who do not.

McKinsey Senior Partner and Asia Financial Services Sales & Distribution Leader Patrick Wu added that AI can only support underlying collaboration, while more complex consultations or after-sales services still require human financial advisors. He noted that for decades, the core competition among financial institutions has centered on the professionalism and productivity of advisory teams, and AI has the potential to enhance both — provided it is embedded at the critical moments that matter most to customers. In his view, the opportunity lies not in simply deploying more software, but in building an AI-powered advisory model that combines enhanced preparation and personalized service with human professional judgment and accountability.

To address these challenges, the report also puts forward four recommendations: first, financial institutions should invest in training, coaching, and reshaping advisor work models with the same intensity as their technology investments; second, since AI's effectiveness depends on its underlying systems, institutions should solidify their data foundations before scaling; third, embed the expertise of top-performing advisors into the systems; and fourth, invest in the human skills that AI cannot replicate.