Half of HK advisers lag behind AI-informed clients

Half of Hong Kong customers have already used AI before they reach a purchase decision, yet half of advisers use AI less than once a week or never, according to a recent survey by McKinsey & Company. 

The survey highlights a widening gap between increasingly AI-informed clients and the advisers serving them. Even as AI reshapes how consumers evaluate options, human advice remains central to major decisions.

Around 80% of customers purchasing life, health, and wealth products still rely primarily on human advisers. Rather than emotional reassurance, clients seek practical value, including personal context, risk avoidance, real-time answers to complex questions, and post-purchase accountability.

This dynamic exposes a two-speed market. Consumers increasingly treat AI as an objective second opinion, relying on it most when identifying protection needs, comparing products, and making final purchase choices. Among those using AI support, nearly 60% cited more consistent comparisons, while over half viewed it as offering stronger product knowledge than human advisers—areas traditionally considered core adviser strengths.

“AI is not removing the need for human advice. It is changing the standard that sound advice must meet,” said Arthur Shek, managing partner of McKinsey & Company’s Hong Kong office. “Customers increasingly arrive with information, comparisons and questions shaped by AI, but they still want human judgment and accountability for consequential decisions. The real divide may therefore emerge between advisers who use AI to raise their game and those who do not.”

The survey suggests low current adviser usage stems from a lack of suitable tools rather than industry reluctance. In situations where advisers do not use AI, the absence of an appropriate tool was cited more frequently than personal discomfort. Adoption rates also vary significantly by client segment, with weekly usage among advisers serving mass, affluent, and high-net-worth clients standing at 34%, 58%, and 69%, respectively. The largest gaps appear in customer-facing activities such as prospecting, closing decisions, and needs analysis.

“The challenge is less about convincing advisers that AI matters, and more about showing them how it creates better outcomes for their clients,” said Jackey Yu, partner and leader of Asia customer experience and AI transformation at McKinsey & Company. “In most activities, the bigger barrier is not resistance, but the absence of tools that fit naturally into advisers’ daily work. Financial services institutions should move beyond standalone tools and focus on a small number of practical, high-impact use cases.”

To address these challenges, McKinsey outlines four priorities for financial institutions:

First, firms must focus on adoption discipline rather than software deployment alone. Success requires investing in training, coaching, and workflow redesign to drive changed behavior and better client outcomes.

Second, institutions need to build a solid data foundation before scaling. Fragmented records and disconnected platforms currently hold back willing advisers, making baseline integration essential for advanced use cases.

Third, organisations should capture the expertise of top-performing advisers within their AI systems. In a complex market such as Hong Kong, embedding elite human judgment into technology elevates overall advisory standards.

Fourth, firms must invest in non-replicable human skills. An adviser’s edge increasingly relies on counseling abilities—listening, building trust, and guiding clients through complex choices. As technology handles information gathering, the quality of human relationships becomes the key differentiator.

“For decades, financial services institutions have competed on the professionalism and productivity of their advisory forces,” said Raymond Woo, partner and leader of Asia financial services sales and distribution at McKinsey & Company. “AI can deliver a step change in both professionalism and productivity — but only when it changes how advisers actually work. The opportunity is not simply to adopt more technology; it is to build an AI-enabled advisory model where AI sharpens preparation and personalisation, and advisers bring the judgment and accountability clients trust."

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